Soft Computing Applications in Industry

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Prasad, Bhanu (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Studies in Fuzziness and Soft Computing, 226
• Θέματα: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

 Softcomputing techniques play a vital role in the industry. This book presents several important papers contributed by some of the well-known scientists from all over the globe. The application domains discussed in this book include: agroecology, bioinformatics, branched fluid-transport network layout design, dam scheduling, data analysis and exploration, detection of phishing attacks, distributed terrestrial transportation, fault detection of motors, fault diagnosis of electronic circuits, fault diagnosis of power distribution systems, flood routing, hazard sensing, health care, industrial chemical processes, knowledge management in software development, local multipoint distribution systems, missing data estimation, parameter calibration of rainfall intensity models, parameter identification for systems engineering, petroleum vessel mooring, query answering in P2P systems, real-time strategy games, robot control, satellite heat pipe design, monsoon rainfall forecasting, structural design, tool condition monitoring, vehicle routing, water network design, etc. The softcomputing techniques presented in this book are on (or closely related to): ant-colony optimization, artificial immune systems, artificial neural networks, Bayesian models, case-based reasoning, clustering techniques, differential evolution, fuzzy classification, fuzzy neural networks, genetic algorithms, harmony search, hidden Markov models, locally weighted regression analysis, probabilistic principal component analysis, relevance vector machines, self-organizing maps, other machine learning and statistical techniques, and the combinations of the above techniques. 

 Optimization of Industrial Processes Using Improved and Modified Differential Evolution -- Noise-Robust Tool Condition Monitoring in Micro-milling with Hidden Markov Models -- Dynamically Self-generated Fuzzy Neural Networks with Industry Applications -- Kernel Estimators in Industrial Applications -- Negative Selection Algorithm with Applications in Motor Fault Detection -- Harmony Search Applications in Industry -- Soft Computing in Bioinformatics: Genomic and Proteomic Applications -- Evolutionary Regression and Neural Imputations of Missing Values -- Glowworm Swarm Optimization Algorithm for Hazard Sensing in Ubiquitous Environments Using Heterogeneous Agent Swarms -- Self-organization in Evolution for the Solving of Distributed Terrestrial Transportation Problems -- Statistical Forecasting of Indian Summer Monsoon Rainfall: An Enduring Challenge -- Fault Diagnosis of Electronic Circuits Using Cellular Automata Based Pattern Classifier -- A Survey of Artificial Neural Network-Based Modeling in Agroecology -- Software Development Knowledge Management Using Case-Based Reasoning -- Learning from Demonstration and Case-Based Planning for Real-Time Strategy Games -- A CBR System: The Core of an Ambient Intelligence Health Care Application -- Soft Query-Answering Computing in P2P Systems with Epistemically Independent Peers -- Power Distribution System Fault Diagnosis Using Hybrid Algorithm of Fuzzy Classification and Artificial Immune Systems -- Detection of Phishing Attacks: A Machine Learning Approach.