INFORMAZIONI SU QUESTO ARTICOLO

Cita

X.S. Lin, Y.F. Chen, C.F. Yang, “Development and Implement of a Cane Sugar Automated System”, Guangxi Sugarcane, China, No. 2, 2008, pp. 39-43.Search in Google Scholar

T. Lu, F. Luo, Z.Y. Mao, C.C. Wen, “Parameters Soft-sensing Based on Neural Network in Crystallizing Process of Cane Sugar”, Proceedings of the 4th World Congress on Intelligent Control and Automation, Vol. 3, 2002, pp. 1944-19448.Search in Google Scholar

Y.M. Meng, H.P. He, F.N. Lu, “Research of a Real-time Soft Sensor System of Syrup Supersaturation in Sugar Crystallization Process”, Journal of Guangxi University (Natural Science Edition), China, Vol. 38, No. 1, 2012, pp. 1-4.Search in Google Scholar

H.P. He, “Research and Application of an Expert System in Sugar Process Based on Rough Set and Support Vector Machine”, Master of Academic Thesis, Faculty of Mechanical Engineering, Guangxi University, China, 2013.Search in Google Scholar

P.F. Bordui, G.M. Loiacono, “In-line bulk supersaturation measurement by electrical conductometry in KDP crystal growth from aqueous solution”, Journal of Crystal Growth, Vol. 67, No. 2, 1984, pp. 168-172.10.1016/0022-0248(84)90175-1Search in Google Scholar

D.D. Dunuwila, K.A. Berglund, “ATR FTIR spectroscopy for in situ measurement of supersaturation”, Journal of Crystal Growth, Vol. 179, No. 1–2, 1997, pp. 185-193.10.1016/S0022-0248(97)00119-XSearch in Google Scholar

A. Markande, J. Fitzpatrick, A. Nezzal, L. Aerts, A. Redl, “Application of in-line monitoring for aiding interpretation and control of dextrose monohydrate crystallization”, Journal of Food Engineering, Vol. 114, No. 1, 2013, pp. 8-13.10.1016/j.jfoodeng.2012.07.029Search in Google Scholar

P. Barrett, B. Glennon, “Characterizing the Metastable Zone Width and Solubility Curve Using Lasentec FBRM and PVM”, Chemical Engineering Research and Design, Vol. 80, No. 7, 2002, pp. 799-805.10.1205/026387602320776876Search in Google Scholar

C. Damour, M. Benne, B.G. Perez, J.P. Chabriat, “Nonlinear predictive control based on artificial neural network model for industrial crystallization”, Journal of Food Engineering, Vol. 99, No. 2, 2010, pp. 225-231.10.1016/j.jfoodeng.2010.02.027Search in Google Scholar

Z.L. Sha, M.L. Kultanen, S. Palosaari, “Neural network simulation for non-MSMPR crystallization”, Chemical Engineering Journal, Vol. 81, No. 1–3, 2001, pp. 101-107.10.1016/S1385-8947(00)00238-2Search in Google Scholar

W. Paengjuntuek, L. Thanasinthana, A. Arpornwichanop, “Neural network-based optimal control of a batch crystallizer”, Neurocomputing, Vol. 83, 2012, pp. 158-164.10.1016/j.neucom.2011.12.008Search in Google Scholar

A. Mesbah, J. Landlust, A.E.M. Huesman, H.J.M. Kramer, P.J. Jansens, P.M.J. Van den Hof, “A model-based control framework for industrial batch crystallization processes”, Chemical Engineering Research and Design, Vol. 88, No. 9, 2010, pp. 1223-1233.10.1016/j.cherd.2009.09.010Search in Google Scholar

G.M. Agusta1, K. Hulliyah, Arini, R.B. Bahaweres, “Applying merging convetional marker and backpropagation neural network in QR code augmented reality tracking”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 5, 2013, pp. 1918-1948.10.21307/ijssis-2017-620Search in Google Scholar

W.L. Li, P. Fu, W.Q. Cao, “Study on feature selection and identification method of tool wear states based on SVM”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 2, 2013, pp. 448-465.10.21307/ijssis-2017-549Search in Google Scholar

Y.M. Huang, Y.S. Duan, “The Design and Implementation of a Distributed Object-oriented Knowledge-based System for Hierarchical Simulation Modeling”, Proceedings. Fourth Annual Conference on AI, Simulation, and Planning in High Autonomy Systems, 1993, pp. 164-17.Search in Google Scholar

G. Li, “Knowledge acquisition method by rough set in the expert system”, Master of Academic Thesis, Xi’an University of Architecture and Technology, China, 2004.Search in Google Scholar

Y.L. Jiang, C.F. Xu, J. Gou, Z.X. Li, “Research on Rough Set Theory Extension and Rough Reasoning”, IEEE International Conference on Systems, Man and Cybernetics, 2004.Search in Google Scholar

J.Y. Wang, C. Gao, “Fast and Complete Algorithm for Reduction Based on Discernable Matrix”, Computer Engineering and Applications, vol. 44, No. 8, 2008, pp. 92-94.Search in Google Scholar

X.D. Miao, S.M. Li, H. Shen, “On-board lane detection system for intelligent vehicle based on monocular vision”, International Journal on Smart Sensing and Intelligent Systems, Vol. 5, No. 4, 2012, pp. 957-972.10.21307/ijssis-2017-517Search in Google Scholar

S. Amin, Wirawan, H. Gamantyo, “A new unequal clustering algorithm using energy-balanced area partitioning for wireless sensor networks”, International Journal on Smart Sensing and Intelligent Systems, Vol. 6, No. 5, 2013, pp. 1808-1829.10.21307/ijssis-2017-616Search in Google Scholar

A.F. Salami, H. Bello-Salau, F. Anwar, A.M. Aibinu, “A novel biased energy distribution (BED) technique for cluster-based routing in wireless sensor networks”, International Journal on Smart Sensing and Intelligent Systems, Vol. 4, No. 2, 2011, pp. 161-173.10.21307/ijssis-2017-433Search in Google Scholar

Y.Q. Wang, L. Liu, “New intelligent classification method based on improved meb algorithm”, International Journal on Smart Sensing and Intelligent Systems, Vol. 7, No. 1, 2014, pp. 72-95.10.21307/ijssis-2017-646Search in Google Scholar

S. Ramathilaga, J. jiunn, Y. Leu, Y.M. Huang, “Adapted Mean Variable Distance to Fuzzy-C means for Effective Image Clustering”, Proceedings. First International conference on Robot, Vision and Signal Processing, Kaohsiung, Taiwan, 2011, pp. 48-51.10.1109/RVSP.2011.58Search in Google Scholar

X.W. Kang, X.S. Sun, S. Wang, Y.Q. Liu, Y. Xia, R. Zhou, Z.X. Wu, Y.J. Jin, “A Fast Accuracy Crystal Identification Method Based on Fuzzy C-Means (FCM) Clustering Algorithm for MicroPET”, Proceedings. First International Conference on BioMedical Engineering and Informatics, Sanya, Hainan, China, 2008, pp. 779-782.10.1109/BMEI.2008.351Search in Google Scholar

H.T. Zhang, H.P. Mao, “Rough Sets Weights Application in the Extension Classification of the Stored-grain Pests Based on Fuzzy C-means Discretization”, Transactions of the Chinese Society for Agricultural Machinery, Vol. 39, No. 7, 2007, pp. 124-128.Search in Google Scholar

Y.M. Luo, P.Z. Liu, M.H. Liao, “An artificial immune network clustering algorithm for mangroves remote sensing image”, International Journal on Smart Sensing and Intelligent Systems, Vol. 7, No. 1, 2014, pp. 116-134.10.21307/ijssis-2017-648Search in Google Scholar

F. Calabrese, A. Corallo, A. Margherita, A.A. Zizzari, “A Knowledge-based Decision Support System for Shipboard Damage Control”, Expert Systems with Applications, Vol. 39, No. 9, 2012, pp. 8204-8211.10.1016/j.eswa.2012.01.146Search in Google Scholar

M. Liu, T. Quan, S. Luan, “An Attribute Recognition System Based on Rough Set Theory-Fuzzy Neural Network and Fuzzy Expert System”, Fifth World Congress on intelligent Control and Automation, Vol. 3, 2004, pp. 2355-2359.Search in Google Scholar

Y.M. Huang, S.H. Lin, “An Efficient Inductive Learning Method for Object-oriented Database Using Attribute Entropy”, IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6, 1996, pp. 946-951.10.1109/69.553161Search in Google Scholar

C.Y. Zhang, “Research on Algorithm for Attribute Value Reduction Based on Rough Set”, Computer and Modernization, China, Vol. 7, 2008, pp. 79-81.Search in Google Scholar

B.B. Qu, “Research on Knowledge Acquisition for Decision Information System Based on Rough Set Theory”, Master of Academic Thesis, Faculty of Computer Science and Technology, Huazhong University of Science and Technology, China, 2006.Search in Google Scholar

L. Peng, “Research on Classification Algorithm of Support Vector Machine and its Application”, Maste of Academic Thesis, Faculty of Electrical and Information Engineering, Hunan University, China, 2007.Search in Google Scholar

J.L. An, Z.O. Wang, Q.X. Yang, Z.P. Ma, C.J. Gao, “Study on Method of On-line Identification for Complex Nonlinear Dynamic System Based on SVM”, Proceedings of International Conference on Machine Learning and Cybernetics, Vol. 3, 2005, pp. 1654-1659.Search in Google Scholar

A. Moosavian, H. Ahmadi, A. Tabatabaeefar, B. Sakhaei, “An appropriate prodedure for detection of journal-bearing fault using power spectral density, K-nearest neighbor and support vector machine”, International Journal on Smart Sensing and Intelligent Systems, Vol. 5, No. 3, 2012, pp. 685-700.10.21307/ijssis-2017-502Search in Google Scholar

F. Ardjani, K. Sadouni, M. Benyettou, “Optimization of SVM MultiClass by Particle Swarm (PSO-SVM)”, Proceedings. Second International Workshop on Database Technology and Application (DBTA), 2010, pp. 1-4.10.1109/DBTA.2010.5658994Search in Google Scholar

Y.D. Wang, J.X. Liu, “Research of Particle Swarm Optimization and its Improvement”, Information and Computer, China, Vol. 3, 2012, pp. 129-130.Search in Google Scholar

W. Jatmiko, W. Pambuko, A. Febrian, P. Mursanto, A. Muis, B. Kusumoputro, K. Sekiyama, T. Fukuda, “Ranged subgroup particle swarm optimization for localizing multiple odor sources”, International Journal on Smart Sensing and Intelligent Systems, Vol. 3, No. 3, 2010, pp. 411-442.10.21307/ijssis-2017-401Search in Google Scholar

J. Manikandan, B. Venkataramani, “Study and Evaluation of a Multiclass SVM Classifier Using Diminishing Learning Technique”, Neurocomputing, Vol. 73, No. 10-12, 2010, pp. 129145.10.1016/j.neucom.2009.11.042Search in Google Scholar

N.K.Suryadevara, A. Gaddam, R.K.Rayudu and S.C. Mukhopadhyay, “Wireless Sensors Network based safe Home to care Elderly People: Behaviour Detection”, Sens. Actuators A: Phys. (2012), doi:10.1016/j.sna.2012.03.020, Volume 186, 2012, pp. 277 – 283.10.1016/j.sna.2012.03.020Search in Google Scholar

J. Luts, F. Ojeda, “A Tutorial on Support Vector Machine-based Methods for Classification Problems in Chemometrics”, Analytica Chimica Acta, Vol. 665, No. 2, 2010, pp. 129-145.10.1016/j.aca.2010.03.03020417323Search in Google Scholar

eISSN:
1178-5608
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Engineering, Introductions and Overviews, other