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Chapter and Conference Paper
Optimal Design of Neural Nets Using Hybrid Algorithms
Selection of the topology of a network and correct parameters for the learning algorithm is a tedious task for designing an optimal Artificial Neural Network (ANN), which is smaller, faster and with a better g...
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Chapter and Conference Paper
Neuro Fuzzy Systems: State-of-the-Art Modeling Techniques
Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive i...
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Chapter and Conference Paper
ALEC: An Adaptive Learning Framework for Optimizing Artificial Neural Networks
In this paper we present ALEC (Adaptive Learning by Evolutionary Computation), an automatic computational framework for optimizing neural networks wherein the neural network architecture, activation function, ...
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Chapter and Conference Paper
MARS: Still an Alien Planet in Soft Computing?
The past few years have witnessed a growing recognition of soft computing technologies that underlie the conception, design and utilization of intelligent systems. According to Zadeh [1], soft computing consists ...
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Chapter and Conference Paper
Hybrid Heuristics for Optimal Design of Artificial Neural Networks
Designing the architecture and correct parameters for the learning algorithm is a tedious task for modeling an optimal Artificial Neural Network (ANN), which is smaller, faster and with a better generalization...
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Chapter and Conference Paper
Is Neural Network a Reliable Forecaster on Earth? A MARS Query!
Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear ...
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Chapter and Conference Paper
Hybrid Intelligent Systems for Stock Market Analysis
The use of intelligent systems for stock market predictions has been widely established. This paper deals with the application of hybridized soft computing techniques for automated stock market forecasting and...
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Chapter and Conference Paper
Global Optimisation of Neural Networks Using a Deterministic Hybrid Approach
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural network, which is smaller, faster and with a better ...
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Chapter and Conference Paper
Soft Computing for Develo** Short Term Load Forecasting Models in Czech Republic
This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system...
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Chapter and Conference Paper
Optimizing Linear Programming Technique Using Fuzzy Logic
The purpose of this paper is to point to the usefulness of applying a linear mathematical formulation of fuzzy multiple criteria objective decision methods in organising business activities. In this respect fu...
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Chapter and Conference Paper
Adaptive Database Learning in Decision Support Systems Using Evolutionary Fuzzy Systems: A Generic Framework
Normally a decision support system is build to solve problem where multi-criteria decisions are involved. The database is the vital part of the decision support containing the information or data that is used ...
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Chapter and Conference Paper
Adaptation of a Mamdani Fuzzy Inference System Using Neuro-genetic Approach for Tactical Air Combat Decision Support System
Normally a decision support system is build to solve problems where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support system containing the information or data...
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Chapter and Conference Paper
A Linear Genetic Programming Approach for Modelling Electricity Demand Prediction in Victoria
Genetic programming (GP), a relatively young and growing branch of evolutionary computation is gradually proving to be a promising method of modelling complex prediction and classification problems. This paper...
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Book and Conference Proceedings
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Chapter and Conference Paper
Canadian Weather Analysis Using Connectionist Learning Paradigms
In this paper, we present a comparative study of different neural network models for forecasting the weather of Vancouver, British Columbia, Canada. For develo** the models, we used one year’s data comprisin...
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Chapter and Conference Paper
Improved Kernel Learning Using Smoothing Parameter Based Linear Kernel
Kernel based learning has found wide applications in several data mining problems. In this paper, we propose a modified classical linear kernel using an automatic smoothing parameter (Sp) selection compared with ...
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Chapter and Conference Paper
Intrusion Detection Using Ensemble of Soft Computing Paradigms
Soft computing techniques are increasingly being used for problem solving. This paper addresses using ensemble approach of different soft computing techniques for intrusion detection. Due to increasing inciden...
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Chapter and Conference Paper
Integrating Ensemble of Intelligent Systems for Modeling Stock Indices
The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well-represented using ensemb...
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Chapter and Conference Paper
A Comparative Study of Fuzzy Classifiers on Breast Cancer Data
In this paper, we examine and compare the performance of four fuzzy rule generation methods on Wisconsin breast cancer data [2]. These methods were reported by Ishibuchi [1]et al. For the diagnosis of breast canc...
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Chapter and Conference Paper
Weather Forecasting Models Using Ensembles of Neural Networks
This paper examines applicability of Hopfield Model (HFM) for weather forecasting in southern Saskatchewan, Canada. The model performance is contrasted with multi-layered perceptron network (MLPN), Elman recur...
