Main Article Content
Abstract
Soft computing is the fusion of different constituent elements. The main aim of this fusion to solve real-world problems, which are not solve by traditional approach that is hard computing. Actually, in our daily life maximum problem having uncertainty and vagueness information. So hard computing fail to solve this problems, because it give exact solution. To overcome this situation soft computing techniques plays a vital role, because it has capability to deal with uncertainty and vagueness and produce approximate result. This paper focuses on application of soft computing techniques over hard computing techniques.
Keywords
Hard computing
Soft computing
Hybrid computing
Industrial applications
Article Details
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How to Cite
Chakraborty, S., Sharma, R. K., & Tewari, P. (2017). APPLICATION OF SOFT COMPUTING TECHNIQUES OVER HARD COMPUTING TECHNIQUES: A SURVEY. International Journal of Students’ Research in Technology & Management, 5(4), 08–17. https://doi.org/10.18510/ijsrtm.2017.542
References
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[5] L. Layuan and L. Chunlin; A multicast routing pro-tocol for clustering mobile ad hoc networks; Computer Communications; 2007, Vol. 30, No. 7, Pg. 1641–1654.
[6] C. Cocks; An identity based encryption scheme based on quadratic residues, in IMA International Conference on Cryptography and Coding; Springer; 2001, Pg. 360–363.
[7] H. Debiao, C. Jianhua, and H. Jin; An id-based proxy signature schemes without bilinear pairings, annals of telecommunications-annals des telecommunications; 2011, Vol. 66, No. 11-12, Pg. 657–662.
[8] S. K. Das and S. Tripathi; Energy Efficient Routing Protocol for MANET Using Vague Set, in Proceedings of Fifth International Conference on Soft Computing for Problem Solving; Springer, 2016, Pg. 235-245, DOI: 10.1007/978-981-10-0448-3_19.
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[10] S. K. Das, S. Tripathi, and A. Burnwal; Intelligent energy competency multipath routing in wanet, in Information Systems Design and Intelligent Applications, Springer, 2015, Pg. 535-543, DOI: 10.1007/978-81-322-2250-7_53.
[11] X. Zhang, X. Zhang, and C. Gu,; A micro-artificial bee colony based multicast routing in vehicular ad hoc net-works, Ad Hoc Networks, 2016.
[12] S. K. Das, A. Kumar, B. Das, and A. Burnwal; Ethics of reducing power consumption in wireless sensor networks using soft computing techniques, International Journal of Advanced Computer Research, 2013, Vol. 3, No. 1, Pg. 301-304.
[13] B. K. Mishra, B. Yadav, S. Jha, and A. Burnwal; Fuzzy set theory approach to model super abrasive grinding process using weighted compensatory operator, International Journal of Research in Computer Applications and Robotics, 2015, Vol. 3, No. 5, Pg. 62-68.
[14] S. Murmu, S. Jha, A. Burnwal, and V. Kumar; A proposed fuzzy logic based system for predicting surface roughness when turning hard faced components, International Journal of Computer Applications, 2015, Vol. 125, No. 4.
[15] Kumar, R. K. Sharma, and A. Burnwal; Energy Consumption Model in Wireless Ad-hoc Networks using Fuzzy Set Theory, Global Journal of Advanced Research, 2015, Vol. 2, No. 2, Pg. 419-426.
[16] Burnwal, A. Kumar, and S. K. Das; Assessment of mathematical modeling in different areas, International Journal of Advanced Technology & Engineering Research, 2013, Vol. 3, No. 3, Pg. 23–26.
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[21] S. K. Das, A. Kumar, B. Das, and A. Burnwal; Ethics of E-Commerce in Information and Communications Technologies, International Journal of Advanced Computer Research, 2013, Vol. 3, No. 1, Pg. 122-124, doi=10.1.1.300.9397.
[22] Gardi, R. Sabatini, and S. Ramasamy; Multi-objective optimisation of aircraft flight trajectories in the atm and avionics context, Progress in Aerospace Sciences, 2016, Vol. 83, Pg. 1–36.
[23] Girish; An efficient hybrid particle swarm optimization algorithm in a rolling horizon framework for the aircraft landing problem, Applied Soft Computing, 2016, Vol. 44, Pg. 200–221.
[24] E. Pecorari, A. Mantovani, C. Franceschini, D. Bassano, L. Palmeri, and G. Rampazzo,; Analysis of the effects of meteorology on aircraft exhaust dispersion and deposition using a lagrangian particle model, Science of The Total Environment, 2016, Vol. 541, Pg. 839–856.
[25] D. Jose, S. Prasad, and V. Sridhar; Intelligent vehicle monitoring using global positioning system and cloud computing, Procedia Computer Science, 2015, Vol. 50, Pg. 440–446.
[26] M. Javidi, B. Abdolhamidzadeh, G. Reniers, and D. Rashtchian; A multivariable model for estimation of vapor cloud explosion occurrence possibility based on a fuzzy logic approach for flammable materials, Journal of Loss Prevention in the Process Industries, 2015, Vol. 33, Pg. 140– 150.
[27] K. Khanna and N. Rajpal; Reconstruction of curves from point clouds using fuzzy logic and ant colony optimization, Neurocomputing, 2015, Vol. 161, Pg. 72–80.
[28] M. Killian, B. Mayer, and M. Kozek; Cooperative fuzzy model predictive control for heating and cooling of build-ings, Energy and Buildings, 2016, Vol. 112, Pg. 130–140.
[29] S. Y. Balaman and H. Selim; Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach, 2016, Journal of Cleaner Production.
[30] Tabanjat, M. Becherif, M. Emziane, D. Hissel, H. Ramadan, and B. Mahmah, Fuzzy logic-based water heating control methodology for the efficiency enhancement of hybrid pv–pem electrolyser systems, International Journal of Hydrogen Energy, 2015, Vol. 40, No. 5, Pg. 2149–2161.
[31] Schirrer, M. Brandstetter, I. Leobner, S. Hauer, and M. Kozek; Nonlinear model predictive control for a heat-ing and cooling system of a low-energy office building, Energy and Buildings, 2016, Vol. 125, Pg. 86–98.
[32] S. K. Das and S. Tripathi; Energy efficient routing protocol for manet based on vague set measurement technique, Procedia Computer Science, 2015, Vol. 58, Pg. 348-355, doi:10.1016/j.procs.2015.08.030.
[33] Zeng and Y. Dong; An improved harmony search based energy-efficient routing algorithm for wireless sensor networks, Applied Soft Computing, 2016, Vol. 41, Pg. 135–147.
[34] G. S. Pavani, A. de Franc¸a Queiroz, and J. C. Pellegrini; Analysis of ant colony optimization-based routing in optical networks in the presence of byzantine failures, Information Sciences, 2016, Vol. 340, Pg. 27–40.
[35] Ari, B. O. Yenke, N. Labraoui, I. Damakoa, and A. Gueroui; A power efficient cluster-based routing algorithm for wireless sensor networks: Honeybees swarm intelligence based approach, Journal of Network and Computer Applications, 2016, Vol. 69, Pg. 77–97.
[36] Y. Liu, H. Xiao, Y. Pan, D. Huang, and Q. Wang; Develop-ment of multiple-step soft-sensors using a gaussian process model with application for fault prognosis, Chemometrics and Intelligent Laboratory Systems, 2016, Vol. 157, Pg. 85–95.
[37] R.-E. Precup, P. Angelov, B. S. J. Costa, and M. Sayed-Mouchaweh; An overview on fault diagnosis and nature-inspired optimal control of industrial process applications, Computers in Industry, 2015, Vol. 74, Pg. 75–94.
[38] W. Li, W. Liu, W. Wu, X. Zhang, Z. Gao, and X. Wu; Fault diagnosis of star-connected auto-transformer based 24-pulse rectifier, Measurement, 2016.
[39] S. Zhang, S. Lu, Q. He, and F. Kong; Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis, Journal of Sound and Vibration, 2016.
[40] Li, Y. Zhou, G. Hu, and C. J. Spanos; Fault detection and diagnosis for building cooling system with a tree-structured learning method, Energy and Buildings, 2016.
[41] P. Radha, G. Chandrasekaran, and N. Selvakumar; Simplifying the powder metallurgy manufacturing process using soft computing tools, Applied Soft Computing, 2015, Vol. 27, Pg. 191–204.
[42] G. DAngelo and S. Rampone; Feature extraction and soft computing methods for aerospace structure defect classification, Measurement, 2016, Vol. 85, Pg. 192–209.
[43] Giret, E. Garcia, and V. Botti; An engineering frame-work for service-oriented intelligent manufacturing systems, Computers in Industry, 2016, Vol. 81, Pg. 116–127.
[44] L. Jiang, D. Walczyk, G. McIntyre, and W. K. Chan; Cost modeling and optimization of a manufacturing system for mycelium-based biocomposite parts, Journal of Manufacturing Systems, 2016, Vol. 41, Pg. 8–20.
[45] M. Algabri, H. Mathkour, H. Ramdane, and M. Alsulaiman; Comparative study of soft computing techniques for mobile robot navigation in an unknown environment, Computers in Human Behavior, 2015, Vol. 50, Pg. 42–56.
[46] S. El Ferik, M. T. Nasir, and U. Baroudi; A behavioral adaptive fuzzy controller of multi robots in a cluster space, Applied Soft Computing, 2016, Vol. 44, Pg. 117–127.
[47] K. Jose and D. K. Pratihar; Task allocation and collision-free path planning of centralized multi-robots system for in-dustrial plant inspection using heuristic methods, Robotics and Autonomous Systems, 2016, Vol. 80, Pg. 34–42.
[48] B.-C. Min, Y. Kim, S. Lee, J.-W. Jung, and E. T. Matson; Finding the optimal location and allocation of relay robots for building a rapid end-to-end wireless communication, Ad Hoc Networks, 2016, Vol. 39, Pg. 23–44.
[49] M. A. H. Cisneros, N. V. R. Sarmiento, C. A. Delrieux, C. Piccolo, and G. M. Perillo; Beach carrying capacity assessment through image processing tools for coastal management, Ocean & Coastal Management, 2016, Vol. 130, Pg. 138–147.
[50] J.-x. Chen, Z.-l. Zhu, C. Fu, L.-b. Zhang, and Y. Zhang; An image encryption scheme using nonlinear inter-pixel computing and swapping based permutation approach, Communications in Nonlinear Science and Numerical Simulation, 2015, Vol. 23, No. 1, Pg. 294–310.
[51] K. Espinoza, D. L. Valera, J. A. Torres, A. Lopez,´ and D. Molina-Aiz; Combination of image processing and artificial neural networks as a novel approach for the identification of Bemisia tabaci and Frankliniella occidentalis on sticky traps in greenhouse agriculture, Computers and Electronics in Agriculture, 2016, Vol. 127, Pg. 495–505.
[52] M. d. M. R. Garc´ıa, J. Garc´ıa-Nieto, and J. F. Aldana-Montes, An ontology-based data integration approach for web analytics in e-commerce, Expert Systems with Applications, 2016, Vol. 63, Pg. 20–34.
[53] F. Ali, K.-S. Kwak, and Y.-G. Kim; Opinion mining based on fuzzy domain ontology and support vector machine: a proposal to automate online review classification, 2016, Applied Soft Computing.
[54] X. Ma, J. Bal, and A. Issa; A fast and economic ontology engineering approach towards improving capability match-ing: Application to an online engineering collaborative platform, Computers in Industry, 2014, Vol. 65, No. 9, Pg. 1264– 1275.
[55] S.-W. Kim, S.-Y. Park, and C. Park; Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers, Advances in Space Research, 2016, Vol. 57, No. 1, Pg. 137-152.
[56] Huo, Y. Xia, K. Lu, and M. Fu; Adaptive fuzzy finite-time fault-tolerant attitude control of rigid spacecraft, Journal of the Franklin Institute, 2015, Vol. 352, No. 10, Pg. 4225-4246.
[57] M. Fakoor, S. M. N. Ghoreishi, and H. Sabaghzadeh; Spacecraft component adaptive layout environment (scale): An efficient optimization tool, Advances in Space Research, 2016.
[58] S. K. Das, A. K. Yadav and S. Tripathi; IE2M: Design of intellectual energy efficient multicast routing protocol for ad-hoc network, Peer-to-Peer Networking and Applications, 2016, Pg. 1-18, DOI 10.1007/s12083-016-0532-6.
[59] S. K. Das and S. Tripathi; Intelligent energy-aware efficient routing for MANET, Wireless Networks, 2016, Pg. 1-21, DOI 10.1007/s11276-016-1388-7.
References
[1] S. K. Das, A. Kumar, B. Das, and A. Burnwal; On soft computing techniques in various areas; Computer Science & Information Technology (CS & IT); 2013, Vol. 3, Pg. 59-68, DOI : 10.5121/csit.2013.3206.
[2] M.-A. El Houssaini, A. Aaroud, A. El Hore, and J. Ben-Othman; Multivariate control chart for the detection of mac layer misbehavior in mobile ad hoc networks; Procedia Computer Science6; 2016, Vol. 83, Pg. 58-65.
[3] K. Chaiyasarn; Damage detection and monitoring for tunnel inspection based on computer vision; PhD thesis, University of Cambridge; 2014.
[4] R. Biradar, S. Manvi, and M. Reddy; Link stability based multicast routing scheme in manet; Computer Networks; 2010, Vol. 54, No. 7, Pg. 1183–1196.
[5] L. Layuan and L. Chunlin; A multicast routing pro-tocol for clustering mobile ad hoc networks; Computer Communications; 2007, Vol. 30, No. 7, Pg. 1641–1654.
[6] C. Cocks; An identity based encryption scheme based on quadratic residues, in IMA International Conference on Cryptography and Coding; Springer; 2001, Pg. 360–363.
[7] H. Debiao, C. Jianhua, and H. Jin; An id-based proxy signature schemes without bilinear pairings, annals of telecommunications-annals des telecommunications; 2011, Vol. 66, No. 11-12, Pg. 657–662.
[8] S. K. Das and S. Tripathi; Energy Efficient Routing Protocol for MANET Using Vague Set, in Proceedings of Fifth International Conference on Soft Computing for Problem Solving; Springer, 2016, Pg. 235-245, DOI: 10.1007/978-981-10-0448-3_19.
[9] S. K. Das, S. Tripathi, and A. Burnwal; Fuzzy based energy efficient multicast routing for ad-hoc network, in Computer, Communication, Control and Information Technology (C3IT), 2015 Third International Conference on, IEEE, 2015, Pg. 1-5, DOI: 10.1109/C3IT.2015.7060126.
[10] S. K. Das, S. Tripathi, and A. Burnwal; Intelligent energy competency multipath routing in wanet, in Information Systems Design and Intelligent Applications, Springer, 2015, Pg. 535-543, DOI: 10.1007/978-81-322-2250-7_53.
[11] X. Zhang, X. Zhang, and C. Gu,; A micro-artificial bee colony based multicast routing in vehicular ad hoc net-works, Ad Hoc Networks, 2016.
[12] S. K. Das, A. Kumar, B. Das, and A. Burnwal; Ethics of reducing power consumption in wireless sensor networks using soft computing techniques, International Journal of Advanced Computer Research, 2013, Vol. 3, No. 1, Pg. 301-304.
[13] B. K. Mishra, B. Yadav, S. Jha, and A. Burnwal; Fuzzy set theory approach to model super abrasive grinding process using weighted compensatory operator, International Journal of Research in Computer Applications and Robotics, 2015, Vol. 3, No. 5, Pg. 62-68.
[14] S. Murmu, S. Jha, A. Burnwal, and V. Kumar; A proposed fuzzy logic based system for predicting surface roughness when turning hard faced components, International Journal of Computer Applications, 2015, Vol. 125, No. 4.
[15] Kumar, R. K. Sharma, and A. Burnwal; Energy Consumption Model in Wireless Ad-hoc Networks using Fuzzy Set Theory, Global Journal of Advanced Research, 2015, Vol. 2, No. 2, Pg. 419-426.
[16] Burnwal, A. Kumar, and S. K. Das; Assessment of mathematical modeling in different areas, International Journal of Advanced Technology & Engineering Research, 2013, Vol. 3, No. 3, Pg. 23–26.
[17] S. K. Das, S. Tripathi, and A. Burnwal; Some relevance fields of soft computing methodology, International Journal of Research in Computer Applications and Robotics, 2014, Vol. 2, Pg. 1-6.
[18] L. A. Zadeh; Fuzzy logic, neural networks, and soft computing, Communications of the ACM, 1994, Vol. 37, No. 3, Pg. 77–85.
[19] S. K. Das, S. Tripathi, and A. Burnwal; Design of fuzzy based intelligent energy efficient routing protocol for WANET, in Computer, Communication, Control and Information Technology (C3IT), 2015, Third International Conference on, IEEE, 2015, Pg. 1-4, DOI: 10.1109/C3IT.2015.7060201.
[20] Burnwal, A. Kumar, and S. K. Das; Assessment of fuzzy set theory in different paradigm, International Journal of Advanced Technology & Engineering Research, 2013, Vol. 3, No. 3, Pg. 16–22.
[21] S. K. Das, A. Kumar, B. Das, and A. Burnwal; Ethics of E-Commerce in Information and Communications Technologies, International Journal of Advanced Computer Research, 2013, Vol. 3, No. 1, Pg. 122-124, doi=10.1.1.300.9397.
[22] Gardi, R. Sabatini, and S. Ramasamy; Multi-objective optimisation of aircraft flight trajectories in the atm and avionics context, Progress in Aerospace Sciences, 2016, Vol. 83, Pg. 1–36.
[23] Girish; An efficient hybrid particle swarm optimization algorithm in a rolling horizon framework for the aircraft landing problem, Applied Soft Computing, 2016, Vol. 44, Pg. 200–221.
[24] E. Pecorari, A. Mantovani, C. Franceschini, D. Bassano, L. Palmeri, and G. Rampazzo,; Analysis of the effects of meteorology on aircraft exhaust dispersion and deposition using a lagrangian particle model, Science of The Total Environment, 2016, Vol. 541, Pg. 839–856.
[25] D. Jose, S. Prasad, and V. Sridhar; Intelligent vehicle monitoring using global positioning system and cloud computing, Procedia Computer Science, 2015, Vol. 50, Pg. 440–446.
[26] M. Javidi, B. Abdolhamidzadeh, G. Reniers, and D. Rashtchian; A multivariable model for estimation of vapor cloud explosion occurrence possibility based on a fuzzy logic approach for flammable materials, Journal of Loss Prevention in the Process Industries, 2015, Vol. 33, Pg. 140– 150.
[27] K. Khanna and N. Rajpal; Reconstruction of curves from point clouds using fuzzy logic and ant colony optimization, Neurocomputing, 2015, Vol. 161, Pg. 72–80.
[28] M. Killian, B. Mayer, and M. Kozek; Cooperative fuzzy model predictive control for heating and cooling of build-ings, Energy and Buildings, 2016, Vol. 112, Pg. 130–140.
[29] S. Y. Balaman and H. Selim; Sustainable design of renewable energy supply chains integrated with district heating systems: A fuzzy optimization approach, 2016, Journal of Cleaner Production.
[30] Tabanjat, M. Becherif, M. Emziane, D. Hissel, H. Ramadan, and B. Mahmah, Fuzzy logic-based water heating control methodology for the efficiency enhancement of hybrid pv–pem electrolyser systems, International Journal of Hydrogen Energy, 2015, Vol. 40, No. 5, Pg. 2149–2161.
[31] Schirrer, M. Brandstetter, I. Leobner, S. Hauer, and M. Kozek; Nonlinear model predictive control for a heat-ing and cooling system of a low-energy office building, Energy and Buildings, 2016, Vol. 125, Pg. 86–98.
[32] S. K. Das and S. Tripathi; Energy efficient routing protocol for manet based on vague set measurement technique, Procedia Computer Science, 2015, Vol. 58, Pg. 348-355, doi:10.1016/j.procs.2015.08.030.
[33] Zeng and Y. Dong; An improved harmony search based energy-efficient routing algorithm for wireless sensor networks, Applied Soft Computing, 2016, Vol. 41, Pg. 135–147.
[34] G. S. Pavani, A. de Franc¸a Queiroz, and J. C. Pellegrini; Analysis of ant colony optimization-based routing in optical networks in the presence of byzantine failures, Information Sciences, 2016, Vol. 340, Pg. 27–40.
[35] Ari, B. O. Yenke, N. Labraoui, I. Damakoa, and A. Gueroui; A power efficient cluster-based routing algorithm for wireless sensor networks: Honeybees swarm intelligence based approach, Journal of Network and Computer Applications, 2016, Vol. 69, Pg. 77–97.
[36] Y. Liu, H. Xiao, Y. Pan, D. Huang, and Q. Wang; Develop-ment of multiple-step soft-sensors using a gaussian process model with application for fault prognosis, Chemometrics and Intelligent Laboratory Systems, 2016, Vol. 157, Pg. 85–95.
[37] R.-E. Precup, P. Angelov, B. S. J. Costa, and M. Sayed-Mouchaweh; An overview on fault diagnosis and nature-inspired optimal control of industrial process applications, Computers in Industry, 2015, Vol. 74, Pg. 75–94.
[38] W. Li, W. Liu, W. Wu, X. Zhang, Z. Gao, and X. Wu; Fault diagnosis of star-connected auto-transformer based 24-pulse rectifier, Measurement, 2016.
[39] S. Zhang, S. Lu, Q. He, and F. Kong; Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis, Journal of Sound and Vibration, 2016.
[40] Li, Y. Zhou, G. Hu, and C. J. Spanos; Fault detection and diagnosis for building cooling system with a tree-structured learning method, Energy and Buildings, 2016.
[41] P. Radha, G. Chandrasekaran, and N. Selvakumar; Simplifying the powder metallurgy manufacturing process using soft computing tools, Applied Soft Computing, 2015, Vol. 27, Pg. 191–204.
[42] G. DAngelo and S. Rampone; Feature extraction and soft computing methods for aerospace structure defect classification, Measurement, 2016, Vol. 85, Pg. 192–209.
[43] Giret, E. Garcia, and V. Botti; An engineering frame-work for service-oriented intelligent manufacturing systems, Computers in Industry, 2016, Vol. 81, Pg. 116–127.
[44] L. Jiang, D. Walczyk, G. McIntyre, and W. K. Chan; Cost modeling and optimization of a manufacturing system for mycelium-based biocomposite parts, Journal of Manufacturing Systems, 2016, Vol. 41, Pg. 8–20.
[45] M. Algabri, H. Mathkour, H. Ramdane, and M. Alsulaiman; Comparative study of soft computing techniques for mobile robot navigation in an unknown environment, Computers in Human Behavior, 2015, Vol. 50, Pg. 42–56.
[46] S. El Ferik, M. T. Nasir, and U. Baroudi; A behavioral adaptive fuzzy controller of multi robots in a cluster space, Applied Soft Computing, 2016, Vol. 44, Pg. 117–127.
[47] K. Jose and D. K. Pratihar; Task allocation and collision-free path planning of centralized multi-robots system for in-dustrial plant inspection using heuristic methods, Robotics and Autonomous Systems, 2016, Vol. 80, Pg. 34–42.
[48] B.-C. Min, Y. Kim, S. Lee, J.-W. Jung, and E. T. Matson; Finding the optimal location and allocation of relay robots for building a rapid end-to-end wireless communication, Ad Hoc Networks, 2016, Vol. 39, Pg. 23–44.
[49] M. A. H. Cisneros, N. V. R. Sarmiento, C. A. Delrieux, C. Piccolo, and G. M. Perillo; Beach carrying capacity assessment through image processing tools for coastal management, Ocean & Coastal Management, 2016, Vol. 130, Pg. 138–147.
[50] J.-x. Chen, Z.-l. Zhu, C. Fu, L.-b. Zhang, and Y. Zhang; An image encryption scheme using nonlinear inter-pixel computing and swapping based permutation approach, Communications in Nonlinear Science and Numerical Simulation, 2015, Vol. 23, No. 1, Pg. 294–310.
[51] K. Espinoza, D. L. Valera, J. A. Torres, A. Lopez,´ and D. Molina-Aiz; Combination of image processing and artificial neural networks as a novel approach for the identification of Bemisia tabaci and Frankliniella occidentalis on sticky traps in greenhouse agriculture, Computers and Electronics in Agriculture, 2016, Vol. 127, Pg. 495–505.
[52] M. d. M. R. Garc´ıa, J. Garc´ıa-Nieto, and J. F. Aldana-Montes, An ontology-based data integration approach for web analytics in e-commerce, Expert Systems with Applications, 2016, Vol. 63, Pg. 20–34.
[53] F. Ali, K.-S. Kwak, and Y.-G. Kim; Opinion mining based on fuzzy domain ontology and support vector machine: a proposal to automate online review classification, 2016, Applied Soft Computing.
[54] X. Ma, J. Bal, and A. Issa; A fast and economic ontology engineering approach towards improving capability match-ing: Application to an online engineering collaborative platform, Computers in Industry, 2014, Vol. 65, No. 9, Pg. 1264– 1275.
[55] S.-W. Kim, S.-Y. Park, and C. Park; Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers, Advances in Space Research, 2016, Vol. 57, No. 1, Pg. 137-152.
[56] Huo, Y. Xia, K. Lu, and M. Fu; Adaptive fuzzy finite-time fault-tolerant attitude control of rigid spacecraft, Journal of the Franklin Institute, 2015, Vol. 352, No. 10, Pg. 4225-4246.
[57] M. Fakoor, S. M. N. Ghoreishi, and H. Sabaghzadeh; Spacecraft component adaptive layout environment (scale): An efficient optimization tool, Advances in Space Research, 2016.
[58] S. K. Das, A. K. Yadav and S. Tripathi; IE2M: Design of intellectual energy efficient multicast routing protocol for ad-hoc network, Peer-to-Peer Networking and Applications, 2016, Pg. 1-18, DOI 10.1007/s12083-016-0532-6.
[59] S. K. Das and S. Tripathi; Intelligent energy-aware efficient routing for MANET, Wireless Networks, 2016, Pg. 1-21, DOI 10.1007/s11276-016-1388-7.
[2] M.-A. El Houssaini, A. Aaroud, A. El Hore, and J. Ben-Othman; Multivariate control chart for the detection of mac layer misbehavior in mobile ad hoc networks; Procedia Computer Science6; 2016, Vol. 83, Pg. 58-65.
[3] K. Chaiyasarn; Damage detection and monitoring for tunnel inspection based on computer vision; PhD thesis, University of Cambridge; 2014.
[4] R. Biradar, S. Manvi, and M. Reddy; Link stability based multicast routing scheme in manet; Computer Networks; 2010, Vol. 54, No. 7, Pg. 1183–1196.
[5] L. Layuan and L. Chunlin; A multicast routing pro-tocol for clustering mobile ad hoc networks; Computer Communications; 2007, Vol. 30, No. 7, Pg. 1641–1654.
[6] C. Cocks; An identity based encryption scheme based on quadratic residues, in IMA International Conference on Cryptography and Coding; Springer; 2001, Pg. 360–363.
[7] H. Debiao, C. Jianhua, and H. Jin; An id-based proxy signature schemes without bilinear pairings, annals of telecommunications-annals des telecommunications; 2011, Vol. 66, No. 11-12, Pg. 657–662.
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