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Feed-Forward Artificial Neural Networks (FFANN) can be trained using Genetic Algorithm (GA). GA offers a stochastic global optimization technique that might suffer from two major shortcomings: slow convergence time and impractical data representation. The effect of these shortcomings is more considerable in case of larger FFANN with larger dataset. Using a(More)
The authors have published earlier a parallel & distributed implementation method for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. Such implementation was intended to address the training of larger pattern-classification problem. The implementation platforms included both a homogeneous and a(More)
The Harmony Search algorithm is relatively a young stochastic meta-heuristic that was inspired from the improvisation process of musicians. HS has been successfully applied as an optimization method in many scientific and engineering fields and was reported to be competitive alternative to many rivals. In this work a new framework is presented for adapting(More)
—There have been numerous biologically inspired algorithms used to train feed-forward artificial neural networks such as generic algorithms, particle swarm optimization and ant colony optimization. The Harmony Search (HS) algorithm is a stochastic meta-heuristic that is inspired from the improvisation process of musicians. HS is used as an optimization(More)
The authors have published earlier a novel technique for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. This paper proposes a parallel and distributed implementation method to speedup the execution time to address the training of larger pattern-classification benchmarking problems. The proposed method(More)
—The hippocampus is a structure in the medial temporal lobe of the brain that is involved in episodic memory function. The texture features of the hippocampus could give better differentiation between Alzheimer's disease and normal controls. The localization of the hippocampus structure in MRI histological images is considered as a multimodal global(More)
This paper presents a work in progress that aims to reduce the overall training and processing time of feed-forward multi-layer neural networks. If the network is large processing is expensive in terms of both; time and space. In this paper, we suggest a cost-effective and presumably a faster processing technique by utilizing a heterogeneous distributed(More)
Potholes, debris, sunken manhole covers and others are common street safety hazards drivers experience daily as they “bump” into them unexpectedly while driving. The repair and maintenance process by municipals is an ongoing effort that requires periodic streets inventory to guarantees safety. Unless someone reports the location of a street(More)