تحسين النتائح
ترتيب حسب
من
الى
الصفحة 2
الصفحة 2
Analysis and Design of Intelligent Systems Using Soft Computing Techniques
This book comprises a selection of papers from IFSA 2007 on new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very important to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, intelligent control, or other application areas.
Advances in Evolutionary Computing for System Design
Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: -Introduction to evolutionary computing in system design - Evolutionary neuro-fuzzy systems - Evolution of fuzzy controllers - Genetic algorithms for multi-classifier design -Evolutionary grooming of traffic -Evolutionary particle swarms -Fuzzy logic systems using genetic algorithms - Evolutionary algorithms and immune learning for neural network-based controller design - Distributed problem solving using evolutionary learning -Evolutionary computing within grid environment -Evolutionary game theory in wireless mesh networks - Hybrid multiobjective evolutionary algorithms for the sailor assignment problem - Evolutionary techniques in hardware optimization
Advances in Evolutionary Algorithms : Theory, Design and Practice
The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated: Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines. Demonstrating the practical use of the suggested road map. Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications. Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain. Opening an important track for multiobjective GEA research that relies on decomposition principle.
Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management
Presents a careful selection of relevant applications of CI methods for transport, logistics, and supply chain management problems. The chapters illustrate the current state-of-the-art in the application of CI methods in these fields and should help and inspire researchers and practitioners to apply and develop efficient methods.
Active Sensor Planning for Multiview Vision Tasks
The book describes some effective strategies to generate a sequence of viewing poses and sensor settings for optimally completing a perception task. Several methods are proposed to solve the problems in both model-based and nonmodel-based vision tasks. For model-based applications, the method involves determination of the optimal sensor placements and a shortest path through these viewpoints for automatic generation of a perception plan.
