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Special Zeszyt on New Developments in Scalable Computing

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Special issue on Innovations in Intelligent Systems and Applications

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Special Thematic Zeszyt on Optimal Codes and Related Topics

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Special Zeszyt With Selected Papers From The Workshop “Two Years Avitohol: Advanced High Performance Computing Applications 2017

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Tom 16 (2016): Zeszyt 6 (December 2016)
Special issue with selection of extended papers from 6th International Conference on Logistic, Informatics and Service Science LISS’2016

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Zeszyt Title: Special Zeszyt on Application of Advanced Computing and Simulation in Information Systems

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Tom 15 (2015): Zeszyt 7 (December 2015)
Special Zeszyt on Information Fusion

Tom 15 (2015): Zeszyt 6 (December 2015)
Special Zeszyt on Logistics, Informatics and Service Science

Tom 15 (2015): Zeszyt 5 (April 2015)
Special Zeszyt on Control in Transportation Systems

Tom 15 (2015): Zeszyt 4 (November 2015)

Tom 15 (2015): Zeszyt 3 (September 2015)

Tom 15 (2015): Zeszyt 2 (June 2015)

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Tom 14 (2014): Zeszyt 5 (December 2014)
Special Zeszyt

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Tom 13 (2013): Zeszyt Special-Zeszyt (December 2013)

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The publishing of the present issue (Tom 13, No 4, 2013) of the journal “Cybernetics and Information Technologies” is financially supported by FP7 project “Advanced Computing for Innovation” (ACOMIN), grant agreement 316087 of Call FP7 REGPOT-2012-2013-1.

Tom 13 (2013): Zeszyt 3 (September 2013)

Tom 13 (2013): Zeszyt 2 (June 2013)

Tom 13 (2013): Zeszyt 1 (March 2013)

Tom 12 (2012): Zeszyt 4 (December 2012)

Tom 12 (2012): Zeszyt 3 (September 2012)

Tom 12 (2012): Zeszyt 2 (June 2012)

Tom 12 (2012): Zeszyt 1 (March 2012)

Informacje o czasopiśmie
Format
Czasopismo
eISSN
1314-4081
Pierwsze wydanie
13 Mar 2012
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

Tom 15 (2015): Zeszyt 2 (June 2015)

Informacje o czasopiśmie
Format
Czasopismo
eISSN
1314-4081
Pierwsze wydanie
13 Mar 2012
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

13 Artykułów
Otwarty dostęp

A Survey of Solving Approaches for Multiple Objective Flexible Job Shop Scheduling Problems

Data publikacji: 03 Jul 2015
Zakres stron: 3 - 22

Abstrakt

Abstract

Many real life scheduling problems can be formulated as Flexible Job Shop Scheduling Problems (FJSSPs) which simultaneously optimize several conflicting criteria. A typical feature of such problems is their high computational complexity. The purpose of this paper is to provide a review of the techniques, developed to solve multiple objective FJSSPs during the last decade. These techniques could be classified into two groups: approaches with application of mathematical models and heuristic approaches. Usually hybrid metaheuristic algorithms are proposed for large dimensional real life problems and they outlay the tendency for the future developments of efficient solution approaches for multiple objective FJSSPs.

Keywords

  • Scheduling problems
  • flexible job shop
  • multiple objectives
  • mathematical models
  • metaheuristic algorithms
Otwarty dostęp

A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm

Data publikacji: 03 Jul 2015
Zakres stron: 23 - 35

Abstrakt

Abstract

Exploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural balance of social networks as a mathematical optimization problem by using swarm intelligence, and an efficient discrete particle swarm optimization algorithm was proposed to solve the modeled optimization problem. To take advantage of the topologies of social networks in the algorithm design, the discrete representation of the particle was redefined, and the discrete particle update principles were redesigned. To validate the efficiency of the proposed algorithm, experiments were conducted using synthetic and real-world social networks. The experiments demonstrate that the proposed algorithm not only achieves a balanced social network structure, but also automatically detects the community topology of networks.

Keywords

  • Particle Swarm Optimization
  • social network
  • structural balance
  • community structure
Otwarty dostęp

Time-Aware and Grey Incidence Theory Based User Interest Modeling for Document Recommendation

Data publikacji: 03 Jul 2015
Zakres stron: 36 - 52

Abstrakt

Abstract

Document recommendation involves the recommendation of documents similar to those that a user has preferred in the past. The Vector Space Model (VSM) is commonly adopted to denote the document objects and user interests. The user interests are extracted from the documents that a user has browsed. The interest degree of the user is calculated using the TF-IDF method, but the time factor is not considered. The recent documents that a user has browsed embody much more his/her interests. This study proposes a time-aware and grey incidence theory based user interest model to improve document recommendation. First, the time-aware user interest model is proposed based on the analysis of the user interests, document objects and user interest knowledge table. Second, a coefficient vector model of the user interest degree is designed using the grey incidence theory to differentiate the main from the minor user interests. The time-aware and grey incidence theory based user interest model is then exploited to produce document recommendations. Finally, the experiment and evaluation metrics are studied. The results show that the model proposed outperforms other related models and recommends more accurate documents to the users.

Keywords

  • Document recommendation
  • time-aware
  • grey incidence theory
  • vector space model
  • personalized information service
Otwarty dostęp

TCMVS: A Novel Trajectory Clustering Technique Based on Multi-View Similarity

Data publikacji: 03 Jul 2015
Zakres stron: 53 - 62

Abstrakt

Abstract

The analysis of moving entities “trajectories” is an important task in different application domains, since it enables the analyst to design, evaluate and optimize navigation spaces. Trajectory clustering is aimed at identifying the objects moving in similar paths and it helps the analysis and obtaining of efficient patterns. Since clustering depends mainly on similarity, the computing similarity between trajectories is an equally important task. For defining the similarity between two trajectories, one needs to consider both the movement and the speed (i.e., the location and time) of the objects, along with the semantic features that may vary. Traditional similarity measures are based on a single viewpoint that cannot explore novel possibilities. Hence, this paper proposes a novel approach, i.e., multi viewpoint similarity measure for clustering trajectories and presents “Trajectory Clustering Based on Multi View Similarity” technique for clustering. The authors have demonstrated the efficiency of the proposed technique by developing Java based tool, called TCMVS and have experimented on real datasets.

Keywords

  • Trajectory clustering
  • Euclidean metric
  • multi-view similarity
  • validation
Otwarty dostęp

Improving Community Detection in Time-Evolving Networks Through Clustering Fusion

Data publikacji: 03 Jul 2015
Zakres stron: 63 - 74

Abstrakt

Abstract

Traditional community detection algorithms are easily interfered by noises and outliers. Therefore, we propose to leverage a clustering fusion method to improve the results of community detection. Usually, there are two issues in clustering ensembles: how to generate efficient diversified cluster members, and how to ensembles the results of all members. Specifically: (1) considering the time evolving characteristic of real world networks, we propose to generate clustering members based on the snapshot of networks, where the split based clustering algorithms are performed; (2) considering the difference in the distribution of the cluster centers in each clustering member and the actual distribution, we ensemble the results based on a maximum likelihood method. Moreover, we conduct experiments to show that our method can discover high quality communities.

Keywords

  • Time-evolving network
  • community detection
  • clustering fusion
  • network snapshot
  • maximum likelihood method
  • Expectation Maximization algorithm.
Otwarty dostęp

A Study on the Approximation of Clustered Data to Parameterized Family of Fuzzy Membership Functions for the Induction of Fuzzy Decision Trees

Data publikacji: 03 Jul 2015
Zakres stron: 75 - 96

Abstrakt

Abstract

This paper investigates the Triangular, Trapezoidal and Gaussian approximation methods for the purpose of induction of Fuzzy Decision Trees (FDT). The generation of FDT is done using a Fuzzy ID3 induction algorithm. In this work three fuzzy partitioning techniques which form the basis for our investigation are given attention, namely Fuzzy C Means clustering (FCM), Grid partitioning and Subtractive clustering (Subclust). Our contribution lies in studying the effect of various approximations on the generation of FDT giving specific attention to the classification accuracy of FDT. In this study we show that the accuracy levels of FDT generated using FCM clustered raw data, bypassing the approximation step, is acceptable and this method has several advantages too. Several computational experiments are conducted and non parametric statistical tests are performed to find if any significant differences exist between the method of bypassing the approximation step and the other methods which include approximation. Ten FDTs are developed and used in this study. These FDT’s differ in their fuzzy partitioning techniques and the approximation methods used.

Keywords

  • Fuzzy decision tree
  • clustering
  • fuzzy membership functions
  • non parametric statistical test.
Otwarty dostęp

Compress-and-Forward for Relay Broadcast Channels without Common Messages

Data publikacji: 03 Jul 2015
Zakres stron: 97 - 110

Abstrakt

Abstract

This paper is connected with compress-and-forward strategy for two-user relay broadcast channels without common messages, where the relay node has private messages from the source, in addition to aiding traditional communication from the source to the destination. For this channel we derive two achievable rate regions based on the compress-and-forward strategy in cases of discrete memoryless channels and Gaussian channels, respectively. The numerical results for Gaussian relay broadcast channel show that the inner bound based on the compress-and-forward strategy improves when all the messages without peeling off any components are compressed and sent to the receiver. It also verifies that the inner bound based on compress-and-forward strategy is better than that based on decode-and-forward strategy, when the relay node is near to the sink node. Moreover, the rate region of the broadcast channel improves considerably when the collaboration between the two receivers is allowed. So the relay node can provide residual resources to help the communication between the source and the sink after its communication rate is satisfied, which gives some insights to select an available relay node in a practical communication system.

Słowa kluczowe

  • Relay broadcast channels
  • relay channels
  • broadcast channels
  • achievable rate region
  • compress-and-forward
Otwarty dostęp

Privacy-Preserving of Check-in Services in MSNS Based on a Bit Matrix

Data publikacji: 03 Jul 2015
Zakres stron: 111 - 118

Abstrakt

Abstract

Check-in service, being one of the most popular services in Mobile Social Network Services (MSNS), has serious personal privacy leakage threats. In this paper check-in sequences of pseudonym users were buffered, and a bit matrix for buffered check-in sequences was built, which can achieve privacy guarantee of k-anonymity. The method guarantees that the number of lost check-in locations is minimized while satisfying users’ privacy requirements. Besides, it also reduces the cost of finding a trajectory k-anonymity set. At last, the results of a set of comparative experiments with (k, δ)-anonymity on real world datasets show the method accuracy and efficiency.

Keywords

  • Privacy preservation
  • location privacy
  • trajectory privacy
  • mobile social networks.
Otwarty dostęp

Trilateral Trust Based Defense Mechanism against DDoS Attacks in Cloud Computing Environment

Data publikacji: 03 Jul 2015
Zakres stron: 119 - 140

Abstrakt

Abstract

Distributed Denial of Service (DDoS) in a Cloud leads to a high rate of overload conditions, which subverts the Data Center (DC) performance and ends up in resource unavailability. This work proposes a “Trilateral Trust mechanism” which helps in detecting different kinds of attack groups at different points of time. It is the direct trust based defense mechanism for segregating legitimate and attack groups from the vast number of incoming requestors. It is a hybrid mechanism of trusts that follows the zero trust approach initially and eventually supports both Mutual trust and Momentary trust. This combinatorial trust mechanism helps in detecting almost all kinds of overload conditions at a cautionary period. Detecting the high rate of an attack at an earlier moment of time could reduce the traffic impact towards DC. The simulation results and profit analysis proved that the mechanism proposed is deployable at an attack-prone DC for resource protection, which would eventually benefit the DC economically as well.

Keywords

  • Cloud computing
  • DDoS
  • Data center
  • Cloud service provider
  • Momentary trust
  • Flash crowd
  • Mutual trust
Otwarty dostęp

Comparative Study of a Super-Twisting Sliding Mode Observer and an Extended Kalman Filter for a Freeway Traffic System

Data publikacji: 03 Jul 2015
Zakres stron: 141 - 158

Abstrakt

Abstract

Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the estimation of traffic state variables (density and speed), using the so called Super- Twisting Sliding Mode Observer (STSM). Several numerical simulations, using simulated and real data, show the relevance of the proposed approach. In addition, a comparative study with the Extended Kalman Filter (EKF) is carried-out. The comparison indices concern convergence and stability, dynamic performance and robustness. The design of the two observers is achieved using a nonlinear second order traffic flow model in the same highway traffic and geometric conditions.

Keywords

  • Super-twisting sliding mode observer
  • extended Kalman filter
  • traffic flow model
Otwarty dostęp

A Controller Combining Positive Velocity Feedback with Negative Angle Feedback for a Two-Wheeled Robot

Data publikacji: 03 Jul 2015
Zakres stron: 159 - 170

Abstrakt

Abstract

The two-wheeled robot is a nonlinear system of multi-variables, higherorder and strong coupling. This paper presented a PID Controller with Double Loops (PCDL) to control the tilt angle and velocity of a two-wheeled robot. The angle controller is the regular negative feedback, while the velocity control is the positive feedback. The Double Loops work cooperatively to endow the system with strong anti-interference ability. The stability of the whole system is analyzed and the criterion of the system stability is developed. The simulation and experiments showed that the two-wheeled robot can self-balance and move at an expected velocity and the system has strong anti-interference ability.

Słowa kluczowe

  • Two-wheeled robot
  • Double Loops
  • positive feedback
  • stability
Otwarty dostęp

Robot Path Planning Based on Improved A* Algorithm

Data publikacji: 03 Jul 2015
Zakres stron: 171 - 180

Abstrakt

Abstract

Due to the characteristic that A* algorithm takes a long time when traversing an OPEN table and a CLOSED table, an improved method is proposed that is a new way of array storing in an OPEN table and a CLOSED table. Compared to the original A* algorithm, the way of array storing accesses the array elements by locating the number ranks each time you visit a specified element, which can be done by only one operation. The original A* algorithm requires the traverse of multiple nodes in order to find a specified element. The experimental results show that the comparison of the improved A* algorithm with the original A* algorithm shows that the operating efficiency is improved by more than 40%. Based on the improved A* algorithm the method preserves the advantages of the original A* algorithm, improving the operating efficiency of A* algorithm.

Keywords

  • A* algorithm
  • path planning
  • grid
  • robot
Otwarty dostęp

An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot

Data publikacji: 03 Jul 2015
Zakres stron: 181 - 191

Abstrakt

Abstract

To solve the problem of local minima and unreachable destination of the traditional artificial potential field method in mobile robot path planning, chaos optimization is introduced to improve the artificial potential field method. The potential field function was adopted as a target function of chaos optimization, and a kind of “two-stage” chaos optimization was used. The corresponding movement step and direction of the robot were achieved by chaos search. Comparison of the improved method proposed in this paper and the traditional artificial potential field method is performed by simulation. The simulation results show that the improved method gets rid of the drawbacks, such as local minima and unreachable goal. Furthermore, the improved method is also verified by building up a physical platform based on “Future Star” robot. The success of the physical experiment indicates that the improved algorithm is feasible and efficient for mobile robot path planning.

Keywords

  • Artificial potential field method
  • chaos optimization
  • path planning
  • mobile robot
13 Artykułów
Otwarty dostęp

A Survey of Solving Approaches for Multiple Objective Flexible Job Shop Scheduling Problems

Data publikacji: 03 Jul 2015
Zakres stron: 3 - 22

Abstrakt

Abstract

Many real life scheduling problems can be formulated as Flexible Job Shop Scheduling Problems (FJSSPs) which simultaneously optimize several conflicting criteria. A typical feature of such problems is their high computational complexity. The purpose of this paper is to provide a review of the techniques, developed to solve multiple objective FJSSPs during the last decade. These techniques could be classified into two groups: approaches with application of mathematical models and heuristic approaches. Usually hybrid metaheuristic algorithms are proposed for large dimensional real life problems and they outlay the tendency for the future developments of efficient solution approaches for multiple objective FJSSPs.

Keywords

  • Scheduling problems
  • flexible job shop
  • multiple objectives
  • mathematical models
  • metaheuristic algorithms
Otwarty dostęp

A Novel Social Network Structural Balance Based on the Particle Swarm Optimization Algorithm

Data publikacji: 03 Jul 2015
Zakres stron: 23 - 35

Abstrakt

Abstract

Exploration of the structural balance of social networks is of great importance for theoretical analysis and practical use. This study modeled the structural balance of social networks as a mathematical optimization problem by using swarm intelligence, and an efficient discrete particle swarm optimization algorithm was proposed to solve the modeled optimization problem. To take advantage of the topologies of social networks in the algorithm design, the discrete representation of the particle was redefined, and the discrete particle update principles were redesigned. To validate the efficiency of the proposed algorithm, experiments were conducted using synthetic and real-world social networks. The experiments demonstrate that the proposed algorithm not only achieves a balanced social network structure, but also automatically detects the community topology of networks.

Keywords

  • Particle Swarm Optimization
  • social network
  • structural balance
  • community structure
Otwarty dostęp

Time-Aware and Grey Incidence Theory Based User Interest Modeling for Document Recommendation

Data publikacji: 03 Jul 2015
Zakres stron: 36 - 52

Abstrakt

Abstract

Document recommendation involves the recommendation of documents similar to those that a user has preferred in the past. The Vector Space Model (VSM) is commonly adopted to denote the document objects and user interests. The user interests are extracted from the documents that a user has browsed. The interest degree of the user is calculated using the TF-IDF method, but the time factor is not considered. The recent documents that a user has browsed embody much more his/her interests. This study proposes a time-aware and grey incidence theory based user interest model to improve document recommendation. First, the time-aware user interest model is proposed based on the analysis of the user interests, document objects and user interest knowledge table. Second, a coefficient vector model of the user interest degree is designed using the grey incidence theory to differentiate the main from the minor user interests. The time-aware and grey incidence theory based user interest model is then exploited to produce document recommendations. Finally, the experiment and evaluation metrics are studied. The results show that the model proposed outperforms other related models and recommends more accurate documents to the users.

Keywords

  • Document recommendation
  • time-aware
  • grey incidence theory
  • vector space model
  • personalized information service
Otwarty dostęp

TCMVS: A Novel Trajectory Clustering Technique Based on Multi-View Similarity

Data publikacji: 03 Jul 2015
Zakres stron: 53 - 62

Abstrakt

Abstract

The analysis of moving entities “trajectories” is an important task in different application domains, since it enables the analyst to design, evaluate and optimize navigation spaces. Trajectory clustering is aimed at identifying the objects moving in similar paths and it helps the analysis and obtaining of efficient patterns. Since clustering depends mainly on similarity, the computing similarity between trajectories is an equally important task. For defining the similarity between two trajectories, one needs to consider both the movement and the speed (i.e., the location and time) of the objects, along with the semantic features that may vary. Traditional similarity measures are based on a single viewpoint that cannot explore novel possibilities. Hence, this paper proposes a novel approach, i.e., multi viewpoint similarity measure for clustering trajectories and presents “Trajectory Clustering Based on Multi View Similarity” technique for clustering. The authors have demonstrated the efficiency of the proposed technique by developing Java based tool, called TCMVS and have experimented on real datasets.

Keywords

  • Trajectory clustering
  • Euclidean metric
  • multi-view similarity
  • validation
Otwarty dostęp

Improving Community Detection in Time-Evolving Networks Through Clustering Fusion

Data publikacji: 03 Jul 2015
Zakres stron: 63 - 74

Abstrakt

Abstract

Traditional community detection algorithms are easily interfered by noises and outliers. Therefore, we propose to leverage a clustering fusion method to improve the results of community detection. Usually, there are two issues in clustering ensembles: how to generate efficient diversified cluster members, and how to ensembles the results of all members. Specifically: (1) considering the time evolving characteristic of real world networks, we propose to generate clustering members based on the snapshot of networks, where the split based clustering algorithms are performed; (2) considering the difference in the distribution of the cluster centers in each clustering member and the actual distribution, we ensemble the results based on a maximum likelihood method. Moreover, we conduct experiments to show that our method can discover high quality communities.

Keywords

  • Time-evolving network
  • community detection
  • clustering fusion
  • network snapshot
  • maximum likelihood method
  • Expectation Maximization algorithm.
Otwarty dostęp

A Study on the Approximation of Clustered Data to Parameterized Family of Fuzzy Membership Functions for the Induction of Fuzzy Decision Trees

Data publikacji: 03 Jul 2015
Zakres stron: 75 - 96

Abstrakt

Abstract

This paper investigates the Triangular, Trapezoidal and Gaussian approximation methods for the purpose of induction of Fuzzy Decision Trees (FDT). The generation of FDT is done using a Fuzzy ID3 induction algorithm. In this work three fuzzy partitioning techniques which form the basis for our investigation are given attention, namely Fuzzy C Means clustering (FCM), Grid partitioning and Subtractive clustering (Subclust). Our contribution lies in studying the effect of various approximations on the generation of FDT giving specific attention to the classification accuracy of FDT. In this study we show that the accuracy levels of FDT generated using FCM clustered raw data, bypassing the approximation step, is acceptable and this method has several advantages too. Several computational experiments are conducted and non parametric statistical tests are performed to find if any significant differences exist between the method of bypassing the approximation step and the other methods which include approximation. Ten FDTs are developed and used in this study. These FDT’s differ in their fuzzy partitioning techniques and the approximation methods used.

Keywords

  • Fuzzy decision tree
  • clustering
  • fuzzy membership functions
  • non parametric statistical test.
Otwarty dostęp

Compress-and-Forward for Relay Broadcast Channels without Common Messages

Data publikacji: 03 Jul 2015
Zakres stron: 97 - 110

Abstrakt

Abstract

This paper is connected with compress-and-forward strategy for two-user relay broadcast channels without common messages, where the relay node has private messages from the source, in addition to aiding traditional communication from the source to the destination. For this channel we derive two achievable rate regions based on the compress-and-forward strategy in cases of discrete memoryless channels and Gaussian channels, respectively. The numerical results for Gaussian relay broadcast channel show that the inner bound based on the compress-and-forward strategy improves when all the messages without peeling off any components are compressed and sent to the receiver. It also verifies that the inner bound based on compress-and-forward strategy is better than that based on decode-and-forward strategy, when the relay node is near to the sink node. Moreover, the rate region of the broadcast channel improves considerably when the collaboration between the two receivers is allowed. So the relay node can provide residual resources to help the communication between the source and the sink after its communication rate is satisfied, which gives some insights to select an available relay node in a practical communication system.

Słowa kluczowe

  • Relay broadcast channels
  • relay channels
  • broadcast channels
  • achievable rate region
  • compress-and-forward
Otwarty dostęp

Privacy-Preserving of Check-in Services in MSNS Based on a Bit Matrix

Data publikacji: 03 Jul 2015
Zakres stron: 111 - 118

Abstrakt

Abstract

Check-in service, being one of the most popular services in Mobile Social Network Services (MSNS), has serious personal privacy leakage threats. In this paper check-in sequences of pseudonym users were buffered, and a bit matrix for buffered check-in sequences was built, which can achieve privacy guarantee of k-anonymity. The method guarantees that the number of lost check-in locations is minimized while satisfying users’ privacy requirements. Besides, it also reduces the cost of finding a trajectory k-anonymity set. At last, the results of a set of comparative experiments with (k, δ)-anonymity on real world datasets show the method accuracy and efficiency.

Keywords

  • Privacy preservation
  • location privacy
  • trajectory privacy
  • mobile social networks.
Otwarty dostęp

Trilateral Trust Based Defense Mechanism against DDoS Attacks in Cloud Computing Environment

Data publikacji: 03 Jul 2015
Zakres stron: 119 - 140

Abstrakt

Abstract

Distributed Denial of Service (DDoS) in a Cloud leads to a high rate of overload conditions, which subverts the Data Center (DC) performance and ends up in resource unavailability. This work proposes a “Trilateral Trust mechanism” which helps in detecting different kinds of attack groups at different points of time. It is the direct trust based defense mechanism for segregating legitimate and attack groups from the vast number of incoming requestors. It is a hybrid mechanism of trusts that follows the zero trust approach initially and eventually supports both Mutual trust and Momentary trust. This combinatorial trust mechanism helps in detecting almost all kinds of overload conditions at a cautionary period. Detecting the high rate of an attack at an earlier moment of time could reduce the traffic impact towards DC. The simulation results and profit analysis proved that the mechanism proposed is deployable at an attack-prone DC for resource protection, which would eventually benefit the DC economically as well.

Keywords

  • Cloud computing
  • DDoS
  • Data center
  • Cloud service provider
  • Momentary trust
  • Flash crowd
  • Mutual trust
Otwarty dostęp

Comparative Study of a Super-Twisting Sliding Mode Observer and an Extended Kalman Filter for a Freeway Traffic System

Data publikacji: 03 Jul 2015
Zakres stron: 141 - 158

Abstrakt

Abstract

Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the estimation of traffic state variables (density and speed), using the so called Super- Twisting Sliding Mode Observer (STSM). Several numerical simulations, using simulated and real data, show the relevance of the proposed approach. In addition, a comparative study with the Extended Kalman Filter (EKF) is carried-out. The comparison indices concern convergence and stability, dynamic performance and robustness. The design of the two observers is achieved using a nonlinear second order traffic flow model in the same highway traffic and geometric conditions.

Keywords

  • Super-twisting sliding mode observer
  • extended Kalman filter
  • traffic flow model
Otwarty dostęp

A Controller Combining Positive Velocity Feedback with Negative Angle Feedback for a Two-Wheeled Robot

Data publikacji: 03 Jul 2015
Zakres stron: 159 - 170

Abstrakt

Abstract

The two-wheeled robot is a nonlinear system of multi-variables, higherorder and strong coupling. This paper presented a PID Controller with Double Loops (PCDL) to control the tilt angle and velocity of a two-wheeled robot. The angle controller is the regular negative feedback, while the velocity control is the positive feedback. The Double Loops work cooperatively to endow the system with strong anti-interference ability. The stability of the whole system is analyzed and the criterion of the system stability is developed. The simulation and experiments showed that the two-wheeled robot can self-balance and move at an expected velocity and the system has strong anti-interference ability.

Słowa kluczowe

  • Two-wheeled robot
  • Double Loops
  • positive feedback
  • stability
Otwarty dostęp

Robot Path Planning Based on Improved A* Algorithm

Data publikacji: 03 Jul 2015
Zakres stron: 171 - 180

Abstrakt

Abstract

Due to the characteristic that A* algorithm takes a long time when traversing an OPEN table and a CLOSED table, an improved method is proposed that is a new way of array storing in an OPEN table and a CLOSED table. Compared to the original A* algorithm, the way of array storing accesses the array elements by locating the number ranks each time you visit a specified element, which can be done by only one operation. The original A* algorithm requires the traverse of multiple nodes in order to find a specified element. The experimental results show that the comparison of the improved A* algorithm with the original A* algorithm shows that the operating efficiency is improved by more than 40%. Based on the improved A* algorithm the method preserves the advantages of the original A* algorithm, improving the operating efficiency of A* algorithm.

Keywords

  • A* algorithm
  • path planning
  • grid
  • robot
Otwarty dostęp

An Improved Path Planning Method Based on Artificial Potential Field for a Mobile Robot

Data publikacji: 03 Jul 2015
Zakres stron: 181 - 191

Abstrakt

Abstract

To solve the problem of local minima and unreachable destination of the traditional artificial potential field method in mobile robot path planning, chaos optimization is introduced to improve the artificial potential field method. The potential field function was adopted as a target function of chaos optimization, and a kind of “two-stage” chaos optimization was used. The corresponding movement step and direction of the robot were achieved by chaos search. Comparison of the improved method proposed in this paper and the traditional artificial potential field method is performed by simulation. The simulation results show that the improved method gets rid of the drawbacks, such as local minima and unreachable goal. Furthermore, the improved method is also verified by building up a physical platform based on “Future Star” robot. The success of the physical experiment indicates that the improved algorithm is feasible and efficient for mobile robot path planning.

Keywords

  • Artificial potential field method
  • chaos optimization
  • path planning
  • mobile robot

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