Genetic Methods Used in Artificial Neural Networks Design
نویسندگان
چکیده
In the Artificial Intelligence field, two areas have attracted a lot of attention in the past years: Artificial Neural Networks (ANN’s) and Genetic Algorithms (GA). The artificial neural networks, by their capacity to learn non-linear relationships between an input and an output space have a lot of applications: modeling and controlling dynamic processes and systems, signal processing, pattern recognition, forecast etc. There are many types of ANN, the most used being the feed forward neural networks and the recurrent neural networks. The design and the training of such ANN’s may be optimized by using genetic techniques. In this paper we present several results related to: feature selection in pattern recognition, optimization of feed-forward neural networks structure and the determinations of the spurious attractors of an associative memory by using evolutionary algorithms.
منابع مشابه
Optimum Design of Liquified Natural Gas Bi-lobe Tanks using Finite Element, Genetic Algorithm and Neural Network
A comprehensive set of ten artificial neural networks is developed to suggest optimal dimensions of type ‘C’ Bi-lobe tanks used in the shipping of liquefied natural gas. Multi-objective optimization technique considering the maximum capacity and minimum cost of vessels are implemented for determining optimum vessel dimensions. Generated populations from a genet...
متن کاملUsing the hybrid Taguchi experimental design method – TOPSIS to identify the most suitable artificial neural networks used in energy forecasting
The use of artificial neural networks (ANN) in forecasting has many applications. Appropriate design of ANN parameters enhances the performance and accuracy of neural network models. Most studies use a trial and error approach in setting the value of ANN parameters. Other methods used to determine the best structure of a neural network only use a single evaluation criterion to determine the ap...
متن کاملForecasting and Sensitivity Analysis of Monthly Evaporation from Siah Bisheh Dam Reservoir using Artificial neural Networks combined with Genetic Algorithm
Evaporation process, the main component of the water cycle in nature, is essential in agricultural studies, hydrology and meteorology, the operation of reservoirs, irrigation and drainage systems, irrigation scheduling and management of water resources. Various methods have been presented for estimating evaporation from free surface including water budget method, evaporation from pan and experi...
متن کاملOptimizing Multiple Response Problem Using Artificial Neural Networks and Genetic Algorithm
This paper proposes a new intelligent approach for solving multi-response statistical optimization problems. In most real world optimization problems, we are encountered adjusting process variables to achieve optimal levels of output variables (response variables). Usual optimization methods often begin with estimating the relation function between the response variable and the control variab...
متن کاملEstimation of Discharge over the Submerged Compound Sharp-Crested Weir using Artificial Neural Networks and Genetic Programming
Truncated sharp crested weirs are used to measure flow rate and control upstream water surface in irrigation canals and laboratory flumes. The main advantages of such weirs are ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for estimation of hydraulic data. In...
متن کاملPareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کامل