Cantitate/Preț
Produs
Total produse
Vezi coșul
Swarm, Evolutionary, and Memetic Computing: First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Chennai, India, December 16-18, 2010, Proceedings de Bijaya Ketan Panigrahi

Swarm, Evolutionary, and Memetic Computing: First International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2010, Chennai, India, December 16-18, 2010, Proceedings: Lecture Notes in Computer Science, cartea 6466

Editat de Bijaya Ketan Panigrahi, Swagatam Das, Ponnuthurai Nagaratnam Suganthan, Subhransu Sekhar Dash
en Limba Engleză Paperback – 22 noi 2010

Ca și Ying Tan în Advances in Swarm Intelligence, editorii acestui volum distilează experiența cercetării de vârf în principii computaționale acționabile, marcând debutul seriei de conferințe SEMCCO. Ne-a atras atenția în mod deosebit rigoarea selecției: dintr-un bazin global de 225 de lucrări, doar cele mai relevante 90 au fost incluse, asigurând un standard academic înalt pentru această ediție inaugurală din Lecture Notes in Computer Science.

Suntem de părere că această lucrare reprezintă o ancoră tehnică pentru domeniul inteligenței colective (swarm intelligence), continuând preocupările editorului Bijaya Ketan Panigrahi pentru aplicarea sistemelor inteligente în inginerie, temă regăsită și în Power Engineering and Intelligent Systems sau Soft Computing: Theories and Applications. Dacă lucrările sale anterioare explorau managementul energiei și procesarea de semnal, volumul de față se concentrează pe mecanisme de optimizare fină.

Structura este organizată în jurul unor aplicații practice complexe, evidențiate încă din cuprins: de la optimizarea traiectoriilor vehiculelor hipersonice și fuziunea senzorilor, până la configurarea antenelor electromagnetice. Subliniem progresia de la fundamentele algoritmilor de evoluție diferențială auto-adaptivă către implementări în medii stochastice și clustering fuzzy. Tonul este strict tehnic, orientat spre cercetători și ingineri care caută soluții pentru probleme de optimizare „hard”, unde algoritmii bio-inspirați oferă o eficiență superioară metodelor clasice.

Citește tot Restrânge

Din seria Lecture Notes in Computer Science

Preț: 91171 lei

Preț vechi: 113964 lei
-20%

Puncte Express: 1368

Carte disponibilă

Livrare economică 30 aprilie-14 mai

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9783642175626
ISBN-10: 3642175627
Pagini: 773
Ilustrații: XVIII, 755 p. 214 illus.
Greutate: 1.08 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

De ce să citești această carte

Recomandăm acest volum cercetătorilor și dezvoltatorilor software care doresc să stăpânească algoritmii evolutivi și computația memetică. Cititorul câștigă acces la studii de caz documentate despre optimizarea sistemelor complexe, de la inginerie aerospațială la senzori inteligenți. Este o resursă fundamentală pentru oricine studiază modul în care biologia poate inspira soluții matematice pentru probleme reale de inginerie.

Descriere scurtă

This LNCS volume contains the papers presented at the First Swarm, Evolutionary and Memetic Computing Conference (SEMCCO 2010) held during December 16–– 18, 2010 at SRM University, Chennai, in India. SEMCCO 2010 marked the beginning of a prestigious international conference series that aims at bringing together researchers from academia and industry to report and review the latest progress in the cutting-edge research on swarm, evolutionary, and memetic computing, to explore new application areas, to design new bio-inspired algorithms for solving specific hard optimization problems, and finally to create awareness on these domains to a wider audience of practitioners. SEMCCO 2010 received 225 paper submissions from 20 countries across the globe. After a rigorous peer-review process involving 610 reviews in total, 90 fu- length articles were accepted for oral presentation at the conference. This corresponds to an acceptance rate of 40% and is intended for maintaining the high standardsof the conference proceedings. The papers included in this LNCS volume cover a wide range of topics in swarm, evolutionary, and memetic computing algorithms and their real-world applications in problems selected from diverse domains of science and engineering.

Cuprins

Self-adaptive Differential Evolution with Modified Multi-Trajectory Search for CEC’2010 Large Scale Optimization.- Differential Evolution Based Ascent Phase Trajectory Optimization for a Hypersonic Vehicle.- Dynamic Grouping Crowding Differential Evolution with Ensemble of Parameters for Multi-modal Optimization.- Empirical Study on Migration Topologies and Migration Policies for Island Based Distributed Differential Evolution Variants.- Differential Evolution Based Fuzzy Clustering.- A Population Adaptive Differential Evolution Strategy to Light Configuration Optimization of Photometric Stereo.- Solving Multi Objective Stochastic Programming Problems Using Differential Evolution.- Multi Sensor Fusion Using Fitness Adaptive Differential Evolution.- Differential Evolution Algorithm with Ensemble of Parameters and Mutation and Crossover Strategies.- Design of Robust Optimal Fixed Structure Controller Using Self Adaptive Differential Evolution.- Electromagnetic Antenna Configuration Optimization Using Fitness Adaptive Differential Evolution.- Analyzing the Explorative Power of Differential Evolution Variants on Different Classes of Problems.- A Self Adaptive Differential Evolution Algorithm for Global Optimization.- Optimization for Workspace Volume of 3R Robot Manipulator Using Modified Differential Evolution.- Adaptive Differential Evolution with p-Best Crossover for Continuous Global Optimization.- A New Particle Swarm Optimization Algorithm for Dynamic Environments.- Power Mutation Embedded Modified PSO for Global Optimization Problems.- PSO Advances and Application to Inverse Problems.- Adaptive and Accelerated Exploration Particle Swarm Optimizer (AAEPSO) for Solving Constrained Multiobjective Optimization Problems.- Expedite Particle Swarm Optimization Algorithm (EPSO) for Optimization of MSA.- Covariance Matrix Adapted Evolution Strategy Based Design of Mixed H2/H??? PID Controller.- Towards a Link between Knee Solutions and Preferred Solution Methodologies.- ARelation-Based Model for Convergence Analysis of Evolutionary Algorithm.- Neural Meta-Memes Framework for Combinatorial Optimization.- An Improved Evolutionary Programming with Voting and Elitist Dispersal Scheme.- Heuristic Algorithms for the L(2,1)-Labeling Problem.- Runtime Analysis of Evolutionary Programming Based on Cauchy Mutation.- Best Hiding Capacity Scheme for Variable Length Messages Using Particle Swarm Optimization.- Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model.- Hybrid PSO Based Integration of Multiple Representations of Thermal Hand Vein Patterns.- Detection and Length Estimation of Linear Scratch on Solid Surfaces Using an Angle Constrained Ant Colony Technique.- An Intelligence Model with Max-Min Strategy for Constrained Evolutionary Optimization.- Parallel Ant-Miner (PAM) on High Performance Clusters.- A Software Tool for Data Clustering Using Particle Swarm Optimization.- An ACO Approach to Job Scheduling in Grid Environment.- Runtime Analysis of (1+1) Evolutionary Algorithm for a TSP Instance.- An Evolutionary Approach to Intelligent Planning.- Substitute Domination Relation for High Objective Number Optimization.- Discrete Variables Function Optimization Using Accelerated Biogeography-Based Optimization.- A Genetic Algorithm Based Augmented Lagrangian Method for Computationally Fast Constrained Optimization.- Evolutionary Programming Improved by an Individual Random Difference Mutation.- Taguchi Method Based Parametric Study of Generalized Generation Gap Genetic Algorithm Model.- EBFS-ICA: An Efficient Algorithm for CT-MRI Image Fusion.- Adaptive Nonlinear Signal Approximation Using Bacterial Foraging Strategy.- Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement.- A Hybrid GA-Adaptive Particle Swarm Optimization Based Tuning of Unscented Kalman Filter for Harmonic Estimation.- Using Social Emotional Optimization Algorithm to Direct Orbits of Chaotic Systems.- A Hybrid ANN-BFOA Approach for Optimization of FDM Process Parameters.- Bio Inspired Swarm Algorithm for Tumor Detection in Digital Mammogram.- A Hybrid Particle Swarm with Differential Evolution Operator Approach (DEPSO) for Linear Array Synthesis.- Sensor Deployment in 3-D Terrain Using Artificial Bee Colony Algorithm.- Novel Particle Swarm Optimization Based Synthesis of Concentric Circular Antenna Array for Broadside Radiation.- A Particle Swarm Optimization Algorithm for Optimal Operating Parameters of VMI Systems in a Two-Echelon Supply Chain.- Enhanced Memetic Algorithm for Task Scheduling.- Quadratic Approximation PSO for Economic Dispatch Problems with Valve-Point Effects.- Fuzzified PSO Algorithm for OPF with FACTS Devices in Interconnected Power Systems.- Co-ordinated Design of AVR-PSS Using Multi Objective Genetic Algorithm.- A Genetic Algorithm Approach for the Multi-commodity, Multi-period Distribution Planning in a Supply Chain Network Design.- Particle Swarm Optimization with Watts-Strogatz Model.- Multi-objective Evolutionary Algorithms to Solve Coverage and Lifetime Optimization Problem in Wireless Sensor Networks.- Offline Parameter Estimation of Induction Motor Using a Meta Heuristic Algorithm.- Performance Evaluation of Particle Swarm Optimization Based Active Noise Control Algorithm.- Solution to Non-convex Electric Power Dispatch Problem Using Seeker Optimization Algorithm.- Swarm Intelligence Algorithm for Induction Motor Field Efficiency Evaluation.- Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation.- Performance Comparison of Attribute Set Reduction Algorithms in Stock Price Prediction - A Case Study on Indian Stock Data.- Dimensionality Reduction and Optimum Feature Selection in Designing Efficient Classifiers.- Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems.- Multi-Objective Optimal Design of Switch Reluctance Motors Using Adaptive Genetic Algorithm.- Genetic Algorithm Approaches to Solve RWA Problem in WDM Optical Networks.- Multi-objective Performance Optimization of Thermo-Electric Coolers Using Dimensional Structural Parameters.- An Artificial Physics Optimization Algorithm for Multi-Objective Problems Based on Virtual Force Sorting Proceedings.- Effective Document Clustering with Particle Swarm Optimization.- A Hybrid Differential Invasive Weed Algorithm for Congestion Management.- Security Constrained Optimal Power Flow with FACTS Devices Using Modified Particle Swarm Optimization.- Tuning of PID Controller Using Internal Model Control with the Filter Constant Optimized Using Bee Colony Optimization Technique.- An Efficient Estimation of Distribution Algorithm for Job Shop Scheduling Problem.- Semantic Web Service Discovery Algorithm Based on Swarm System.- Stochastic Ranking Particle Swarm Optimization for Constrained Engineering Design Problems.- A New Improved Particle Swarm Optimization Technique for Daily Economic Generation Scheduling of Cascaded Hydrothermal Systems.- Improved Real Quantum Evolutionary Algorithm for Optimum Economic Load Dispatch with Non-convex Loads.- Linear Array Geometry Synthesis with Minimum Side Lobe Level and Null Control Using Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search.- Constraint Handling in Transmission Network Expansion Planning.- A Novel Multi-objective Formulation for Hydrothermal Power Scheduling Based on Reservoir End Volume Relaxation.- Particle Swarm Optimization and Varying Chemotactic Step-Size Bacterial Foraging Optimization Algorithms Based Dynamic Economic Dispatch with Non-smooth Fuel Cost Functions.- Hydro-thermal Commitment Scheduling by Tabu Search Method with Cooling-Banking Constraints.