This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Gezici S, Tian Z, Giannakis G B, Kobayashi H, Molisch A F, Poor H V and Sahinoqlu Z, “Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks”, IEEE Signal Processing, vol. 22, no. 4, pp. 70-84, 2005.10.1109/MSP.2005.1458289Search in Google Scholar
Patwari N, Ash J N, Kyperountas S, Hero A O, Moses R L and Correal N S, “Locating the nodes: cooperative localization in wireless sensor networks”, IEEE Signal Processing, vol. 22, no. 4, pp. 54-69, 2005.10.1109/MSP.2005.1458287Search in Google Scholar
Biswas P, Lian T C and Wang T C, “Semi-definite programming based algorithms for sensor localization”, ACM Trans Sensor Networks, vol. 2, no. 2, pp. 188-200, 2006.10.1145/1149283.1149286Search in Google Scholar
Kushki A, Plataniotis K and Venetsanopoulos A, “Intelligent dynamic radio tracking in indoor wireless local area networks”, IEEE Transactions on Mobile Computing, vol. 9, no. 3, pp. 405419, 2010.Search in Google Scholar
Ahn H S and Yu W, “Environmental adaptive RSSI based indoor localization”, Automation Science and Engineering, vol. 6, no. 10, pp. 626-633, 2009.10.1109/TASE.2008.2009126Search in Google Scholar
Gurrieri L E, Willink T J, Petosa A and Noghanian S, “Characterization of the angle, delay and polarization of multipath signals for indoor environments”, Antennas and Propagation, vol. 56, no. 8, pp. 2710-2719, 2008.Search in Google Scholar
M. Roseline Juliana and S.Srinivasan, “Seladg: secure energy efficient location aware data gathering approach for wireless sensor networks”, International Journal On Smart Sensing and Intelligent Systems(S2IS), vol. 8, no. 3, pp. 1748-1767, 2015.Search in Google Scholar
Ahadul Imam, Justin Chi and Mohammad Mozumdar, “Data compression and visualization for wireless sensor networks”, International Journal On Smart Sensing and Intelligent Systems(S2IS), vol. 8, no. 4, pp. 2083-2115, 2015.Search in Google Scholar
Yi Zhao, Valentin Gies and Jean-Marc Ginoux, “WSN based thermal modeling: a new indoor energy efficient solution”, International Journal On Smart Sensing and Intelligent Systems(S2IS), vol. 8, no. 2, pp. 869-895, 2015.10.21307/ijssis-2017-787Search in Google Scholar
Sayed A H, Tarighat A and Khajehnuri N, “Networked based wireless location”. IEEE Signal Process, vol. 22, no. 4, pp. 24-40, 2005.10.1109/MSP.2005.1458275Search in Google Scholar
Li Xinrong. “RSS-based location estimation with unknowm pathloss model”. IEEE Transactions on Wireless Communications, vol. 5, no. 12, pp. 3626-3633, 2006.10.1109/TWC.2006.256985Search in Google Scholar
Shang Y, Ruml W, Zhang Y and Fromherz M, “Localization from connectivity in sensor networks”, IEEE Transactions on Parallel and Distributed Systems, vol. 15, no. 11, pp. 961-974, 2004.10.1109/TPDS.2004.67Search in Google Scholar
Jian Y, Frangi A F, Jing-Yu Y,Zhang D and Zhong J, “KPCA plus LDA: a complete kernel fisher disctiminant framework for feature extraction and recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 2, pp. 230-244, 2005.10.1109/TPAMI.2005.3315688560Search in Google Scholar
Natarajan U, Periasamy V M and Aravanan R, “Application of particle swarm optimisation in artificial neural network for the prediction of tool life”, The International Journal of Advanced Manufacturing Technology, vol. 31, no. 9, pp. 871-876, 2007.10.1007/s00170-005-0252-1Search in Google Scholar
Lahiri S K and Ghanta K C, “Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines”, Chemical Engineering Science, vol. 63, no. 1, pp. 1497-1509, 2007.Search in Google Scholar
D. Riordan, P. Doody and J. Walsh, “The use of artificial neural networks in the estimation of the perception of sound by the hunman auditory system”, vol. 8, no. 3, pp. 1806-1836, 2015.Search in Google Scholar
Alcala C F and Qin S J, “Reconstruction-based contribution for process monitoring with kernel principal component analysis”, Industrial and Engineering Chemistry Research, vol. 49, pp. 7849-7857, 2010.Search in Google Scholar
Wei Jing Wonga, Andrew B.J. Teohb, Yau Hee Khoc and M.L. Dennis Wonga, “Kernel PCA enabled bit-string representation for minutiae-based cancellable fingerprint template”, Pattern Recognition, vol. 51, pp. 197-208, 2016.10.1016/j.patcog.2015.09.032Search in Google Scholar
Jian Huang and Xuefeng Yan, “Related and independent variable fault detection based on KPCA and SVDD”, Journal of Process Control, vol. 39, pp. 88-99, 2016.10.1016/j.jprocont.2016.01.001Search in Google Scholar
Majdi Mansouri, Mohamed Nounou, Hazem Nounou and Nazmul Karim, “Kernel PCA-based GLRT for nonlinear fault detection of chemical processes”, Journal of Loss Prevention in the Process Industries, vol. 40, pp. 334-347, 2016.10.1016/j.jlp.2016.01.011Search in Google Scholar
Sakuntala Mahapatra, Raju Daniel, Deep Narayan Dey and Santanu Kumar Nayak, “Induction Motor Control Using PSO-ANFIS”, Procedia Computer Science, vol. 48, pp. 753768, 2015.Search in Google Scholar
Haidar Samet, Farid Hashemi and Teymoor Ghanbari, “Minimum non detection zone for islanding detection using an optimal Artificial Neural Network algorithm based on PSO”, Renewable and Sustainable Energy Reviews, vol. 52, pp. 1-18, 2015.10.1016/j.rser.2015.07.080Search in Google Scholar
Abhijit Suresh, K.V. Harish and N. Radhika, “Particle swarm optimization over back propagation neural network for length of stay prediction”, vol. 46, pp. 268-275, 2015.10.1016/j.procs.2015.02.020Search in Google Scholar
Li Deng, Gen Lu, Yuying Shao, Minrui Fei, Huosheng Hu, “A novel camera calibration technique based on differential evolution particle swarm optimization algorithm”, vol. 174, no. 22, pp. 456-465, 2016.10.1016/j.neucom.2015.03.119Search in Google Scholar
