Business and Social Behaviour Intelligence Analysis Using PSO
DOI:
https://doi.org/10.9781/ijimai.2014.268Keywords:
Artificial Intelligence, Geographic information system, Optimization, PSOAbstract
The goal of this paper is to elaborate swarm intelligence for business intelligence decision making and the business rules management improvement. The paper introduces the decision making model which is based on the application of Artificial Neural Networks (ANNs) and Particle Swarm Optimization (PSO) algorithm. Essentially the business spatial data illustrate the group behaviors. The swarm optimization, which is highly influenced by the behavior of creature, performs in group. The Spatial data is defined as data that is represented by 2D or 3D images. SQL Server supports only 2D images till now. As we know that location is an essential part of any organizational data as well as business data: enterprises maintain customer address lists, own property, ship goods from and to warehouses, manage transport flows among their workforce, and perform many other activities. By means to say a lot of spatial data is used and processed by enterprises, organizations and other bodies in order to make the things more visible and self-descriptive. From the experiments, we found that PSO is can facilitate the intelligence in social and business behaviourDownloads
References
[1] A. Janecek, T. Jordan and F. B. Lima-Neto, “Agent-Based Social Simulation and PSO,” Advances in Swarm Intelligence. Springer Berlin Heidelberg, pp. 63-73, 2013.
[2] J. Kennedy, “Particle swarm optimization,” In Encyclopedia of Machine Learning, Springer US, pp. 760-766, 2010.
[3] M. G. Epitropakis, P. P.Vassilis and N. V. Michael, “Evolving cognitive and social experience in particle swarm optimization through differential evolution,” IEEE Congress on Evolutionary Computation (CEC), 2010.
[4] P. Soni and M. Choudhary, “Hybrid Computational Intelligence for Optimization Based On PSO and DE,” International Journal of Advanced Research in Computer Engineering & Technology, pp-265, 2012.
[5] H. Ahmed and G. Janice, “Swarm Intelligence: Concepts, Models and Applications,” Technical Report, 2012-585. Queen's University, Kingston, Ontario, Canada K7L3N6, 2012.
[6] S.R. Dubey and A.S. Jalal, “Robust Approach for Fruit and Vegetable Classification”, Procedia Engineering, 38, pp. 3449-3453, 2012.
[7] A. E. Yilmaz, “Swarm Behavior of the Electromagnetics Community as regards Using Swarm Intelligence in their Research Studies,” Acta Polytechnica Hungarica, 2010.
[8] S.R. Dubey and A.S. Jalal, “Detection and Classification of Apple Fruit Diseases Using Complete Local Binary Patterns”, In Third International Conference on Computer and Communication Technology, pp. 346-351, 2012.
[9] J. P. Gupta, N. Singh, P. Dixit, V. B. Semwal, and S. R. Dubey, “Human Activity Recognition using Gait Pattern,” International
Journal of Computer Vision and Image Processing, vol. 3, no. 3, pp. 31–53, 2013.
[10] M. Sati, V. Vikash, V. Bijalwan, P. Kumari, M. Raj, M. Balodhi, P. Gairola and V.B. Semwal, “A fault-tolerant mobile computing model based on scalable replica”, International Journal of Interactive Multimedia and Artificial Intelligence, 2014.
[11] K.K. Susheel, V.B. Semwal and R.C. Tripathi, “Real time face recognition using adaboost improved fast PCA algorithm,” arXiv preprint arXiv:1108.1353 (2011).
[12] K.S. Kumar, V.B. Semwal, S. Prasad and R.C. Tripathi, “Generating 3D Model Using 2D Images of an Object,” International Journal of Engineering Science, 2011.
[13] N. Singh, S.R. Dubey, P. Dixit and J.P. Gupta, “Semantic Image Retrieval by Combining Color, Texture and Shape Features,” In the Proceedings of the International Conference on Computing Sciences, pp. 116-120, 2012.
[14] V.B. Semwal, V.B. Semwal, M. Sati and S. Verma, “Accurate location estimation of moving object in Wireless Sensor network,” International Journal of Interactive Multimedia and Artificial Intelligence, vol. 1, no. 4 , pp. 71-75, 2011.
[15] S.R. Dubey and A.S. Jalal, “Adapted Approach for Fruit Disease Identification using Images,” International Journal of Computer Vision and Image Processing, vol. 2, no. 3, pp. 44-58, 2012.
[16] S. Singh and V. Bijalwan, “Design Of Wireless Sensor Network Node On Zigbee For Water Level Detection”, Vol. 3, No. 8, 2013.
[17] A. Bijalwan and V. Bijalwan, “Examining the Crimninology using Network Forensic”, National Conference USCSTC, 2013.
[18] V. Bijalwan, V. Kumar, P. Kumari and J. Pascual, “KNN based Machine Learning Approach for Text and Document Mining”,
International Journal of Database Theory and Application, Vol. 7, No. 1, pp. 61-70, 2014.
[19] P. Kumari and V. Pareek, “RAKSHITA- A Novel web based Approach for Protecting Digital Copyrights Using Public Key Digital Watermarking and Human Fingerprints”, International conference on methods and models in computer science, 2010.
[20] P. Kumari and A. Vaish, “Instant Face detection and attributes recognition” International Journal of Advanced Computer Science and Applications, 2011.
[21] P. Kumari and A. Vaish, “A Comparative study of Machine Learning algorithms for Emotion State Recognition through
Physiological signal”, Advances in Intelligent Systems and Computing, Vol. 236, 2013.
[22] P. Kumari and A. Vaish, “Brainwave’s Energy feature Extraction using wavelet Transform”, proceeding of IEEE SCEECS, 2014.
[23] V.B. Semwal, K.S. Kumar, V.S. Bhaskar and M. Sati, “Accurate location estimation of moving object with energy constraint & adaptive update algorithms to save data”, arXiv preprint arXiv:1108.1321, 2011.
[24] J.P. Espada et al., “Virtual Objects on the Internet of Things”, International Journal of Interactive Multimedia and Artificial
Intelligence, 2011.
[25] R.G. Crespo, S.R. Aguilar, R.F. Escobar and N. Torres, “Dynamic, ecological, accessible and 3D Virtual Worlds-based Libraries using OpenSim and Sloodle along with mobile location and NFC for checking in”, International Journal of Interactive Multimedia & Artificial Intelligence, Vol. 1, No. 7, 2012.
[26] K.S. Kumar et al, “Sports Video Summarization using Priority Curve Algorithm”, International Journal on Computer Science & Engineering, 2010.
[27] R.G. Crespo et al., “Use of ARIMA mathematical analysis to model the implementation of expert system courses by means of free software OpenSim and Sloodle platforms in virtual university campuses”, Expert Systems with Applications, Vol. 40, No. 18, pp. 7381-7390, 2013.
[28] S.R. Dubey, P. Dixit, N. Singh, and J.P. Gupta, “Infected fruit part detection using K-means clustering segmentation technique”, International Journal of Artificial Intelligence and Interactive Multimedia, Vol. 2, No. 2, 2013.
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