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1996, 1, ISBN 9780849394676, xx, 314
Solving pattern recognition problems involves an enormous amount of computational effort. By applying genetic algorithms - a computational method based on the... 
Pattern perception | Machine learning | Genetic algorithms | Mathematics & Statistics for Engineers | Intelligent Systems | Computer Graphics & Visualization
Book
2017, ISBN 9781482298758, xxx, 284 pages
This book uses tutorials and new material to describe the basic concepts of soft-computing which potentially can be used in real-life sensor network... 
Wireless sensor networks | Soft computing | Computer programs | Digital & Wireless Communication | Networks | Computation | COMPUTERSCIENCEnetBASE | ElectricalEngineeringnetBASE | neural | STMnetBASE | SCI-TECHnetBASE | INFORMATIONSCIENCEnetBASE | approaches | smart | ENGnetBASE | node | artificial | safe | vector | wireless | place | support | Wireless sensor networks - Computer programs
Book
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 09/2016, Volume 27, Issue 9, pp. 1890 - 1906
Journal Article
by Kumar, A and Vinod Kumar, A M and Jash, Abhik and Mohanty, Ajit K and Chacko, Aleena and Ajmi, Ali and Ghosal, Ambar and Khatun, Amina and Raychaudhuri, Amitava and Dighe, Amol and Chatterjee, Animesh and Gaur, Ankit and Ghosh, Anushree and Kumar, Ashok and Redij, Asmita and Satyanarayana, B and Acharya, B S and Choudhary, Brajesh C and Ranganathaiah, C and Ravikumar, C D and Gupta, Chandan and Indumathi, D and Kaur, Daljeet and Majumdar, Debasish and Samuel, Deepak and Tiwari, Deepak and Rajasekaran, G and Gangopadhyay, Gautam and Majumder, Gobinda and Ravikumar, H B and Singh, J B and Shahi, J S and Libby, James and Singh, Jyotsna and Raveendrababu, K and Meghna, K K and Rebin, K R and Kar, Kamalesh and Bhattacharya, Kolahal and Pant, Lalit M and Athar, M Sajjad and N Murthy, M V and Malik, Manzoor A and Naimuddin, Md and Salim, Mohammad and Ghosh, Monojit and Devi, Moon Moon and Mondal, Naba K and Majumdar, Nayana and Sinha, Nita and Dash, Nitali and Ghoshal, Pomita and Mehta, Poonam and Behera, Prafulla and Kanishka, R and Gandhi, Raj and Ganai, Rajesh and Hasan, Rashid and Krishnaveni, S and Lakshmi, S M and Singh, S K and R Inbanathan, S S and Sankar, S Uma and Jafer, Sadiq and Biswas, Saikat and Kumar, Sanjeev and Agarwalla, Sanjib Kumar and Choubey, Sandhya and Saha, Satyajit and Ahmed, Shakeel and Behera, Shiba Prasad and Goswami, Srubabati and Chattopadhyay, Subhasis and Bhattacharya, Sudeb and Banerjee, Sudeshna and Dasgupta, Sudeshna and Pal, Sumanta and Mukhopadhyay, Supratik and Raut, Sushant and Bose, Suvendu and Mahapatra, Swapna and Ghosh, Tapasi and Thakore, Tarak and S Kashyap, V K and Subrahmanyam, V S and Singh, Venktesh and Chandratre, Vinay B and Bhatnagar, Vipin and Datar, Vivek M and Bari, Waseem and Viyogi, Y P
Pramāṇa, ISSN 0973-7111, 04/2017, Volume 88, Issue 5, p. 1
The upcoming 50 kt magnetized iron calorimeter (ICAL) detector at the India-based Neutrino Observatory (INO) is designed to study the atmospheric neutrinos and... 
Atmospheric neutrinos | India-based neutrino observatory | Neutrino physics | Neutrino experiments | Physics, Multidisciplinary | Physical Sciences | Physics | Science & Technology
Journal Article
Journal of applied mathematics & computing, ISSN 1865-2085, 09/2015, Volume 52, Issue 1-2, pp. 37 - 57
Journal Article
eBook
Information sciences, ISSN 0020-0255, 09/2015, Volume 314, pp. 100 - 117
Social network data has been modeled with several approaches, including Sociogram and Sociomatrices, which are popular and comprehensive. Similar to these we... 
Community detection | Influence maximization | Entropy | Big data | Granular computing | Fuzzy set | Computer Science, Information Systems | Technology | Computer Science | Science & Technology | Social networks | Models | Fuzzy logic | Communities | Granular materials | Granules | Fuzzy set theory | Fuzzy
Journal Article
12/2016, ISBN 9789813144545
Book
2010, ISBN 9781439803295, 1 v. (various pagings)
Book
Fundamenta informaticae, ISSN 0169-2968, 2007, Volume 80, Issue 4, pp. 475 - 496
A hybrid unsupervised learning algorithm, termed as rough-fuzzy c-means, is proposed in this paper. It comprises a judicious integration of the principles of... 
Pattern recognition | Clustering | Data mining | Rough sets | Fuzzy c-means | Physical Sciences | Technology | Computer Science | Mathematics | Computer Science, Software Engineering | Mathematics, Applied | Science & Technology
Journal Article