Chapter 6. Neuro-Genetic Information Processing for Optimisation and Adaptation in Intelligent Systems
نویسندگان
چکیده
This chapter describes the intersection of two areas of artificial intelligence research, genetic algorithms and neural networks. The chapter has six main sections. The first describes the motivation for this research, which is followed by a gentle introduction to the basic principles of genetic algorithms. The third section deals with the application of genetic algorithms to conventional neural networks, while the fourth continues this into neurofuzzy systems. The fifth section describes some advanced neurogenetic systems and suggests a new model for this. Finally, the conclusion reviews the preceding sections.
منابع مشابه
Indirect Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control for a Class of Uncertain Nonlinear Systems
Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...
متن کاملOptimisation of assembly scheduling in VCIM systems using genetic algorithm
Assembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the application of traditional computer-integrated manufacturing (CIM) system to global level. Assembly scheduling in VCIM systems is ...
متن کاملA Comparative Study of the Neural Network, Fuzzy Logic, and Nero-fuzzy Systems in Seismic Reservoir Characterization: An Example from Arab (Surmeh) Reservoir as an Iranian Gas Field, Persian Gulf Basin
Intelligent reservoir characterization using seismic attributes and hydraulic flow units has a vital role in the description of oil and gas traps. The predicted model allows an accurate understanding of the reservoir quality, especially at the un-cored well location. This study was conducted in two major steps. In the first step, the survey compared different intelligent techniques to discover ...
متن کاملAdaptive Network-based Fuzzy Inference System-Genetic Algorithm Models for Prediction Groundwater Quality Indices: a GIS-based Analysis
The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...
متن کاملLoss of Load Expectation Assessment in Deregulated Power Systems Using Monte Carlo Simulation and Intelligent Systems
Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. Also, because of power market and generators’ forced outages stochastic behavior, Monte Carlo Simulation is used for reliability evaluation. Generation r...
متن کامل