Soft Computing Methods for Practical Environment Solutions: Techniques and Studies: Techniques and StudiesGestal Pose, Marcos, Rivero Cebri n, Daniel Nature provides inspiration and guidance in the creation of techniques, applications and new technologies in the fields of Artificial Intelligence and Soft Computing. Soft Computing Methods for Practical Environment Solutions: Techniques and Studies presents various practical applications of Soft Computing techniques in real-world situations and problems, aiming to show the enormous potential of such techniques in solving all kinds of problems, and thus, providing the latest advances in these techniques in an extensive state-of-the-art and a vast theoretical study. Ideal for students studying AI and researchers familiarizing themselves with such techniques, so to offer recent and novel applications, helping expand and explore new areas of research. |
Contents
1 | |
Artificial Cell Model Used forInformation Processing | 12 |
Soft Computing Techniques forHumanComputer Interaction | 30 |
LVQ Neural Networks inColor Segmentation | 45 |
A Descriptive Overview | 64 |
User Modeling in SoftComputing Framework | 75 |
Electromagnetic OptimizationUsing Genetic Algorithms | 93 |
A PROMETHEE and TrigonometricDifferential Evolution Analysisof their Chemical Emissions | 106 |
GABased Data Mining Appliedto Genetic Data for theDiagnosis of Complex Diseases | 219 |
Improving Ontology Alignmentthrough Genetic Algorithms | 240 |
Characterization andModelization of SurfaceNet Radiation throughNeural Networks | 260 |
Application of Machine LearningTechniques in the Study of theRelevance of EnvironmentalFactors in Prediction ofTropospheric Ozone | 278 |
Evolutionary LagrangianInverse Modeling for PM10Pollutant Dispersion | 293 |
Artificial Intelligence Applied toNatural Resources Management | 313 |
Applications of SelfOrganizing Maps to AddressEnvironmental Studies | 331 |
Neural Models forRainfall Forecasting | 353 |
A Soft Computing System forModelling the Manufactureof Steel Components | 127 |
Time Series Prediction | 143 |
Intrinsic EvolvableHardware Structures | 160 |
Connectionist Systems andSignal Processing TechniquesApplied to the Parameterizationof Stellar Spectra | 187 |
Automatic Arrhythmia Detection | 204 |