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One of the aims of the Protein Structure Initiative (PSI) in the post genome-sequencing era is to elucidate biochemical and biophysical functions of each protein structure. Thus, the development of new methods for a large-scale analysis/annotation of protein functional residues is inevitable. Currently existing methods are not capable to do so due to the lack of automation, availability, and/or poor...
In recent years there is a growing interest around minimax probability machine (MPM) whose performance depends on its kernel function. Considering that the Euclidean distance has a natural generalization in form of the Minkovskypsilas distance, we replace the Euclidean distance in the Gaussian kernel with a more generalized Minkovskypsilas distance. This paper presents an empirical study for MPM prediction...
Online auctions have become extremely popular in recent years. Ability to predict winning bid prices accurately can help bidders to maximize their profit. This paper proposes a number of strategies and algorithms for performing such predictions for the first price sealed bid reverse auctions (FPSBRA). The neural networks (NN) and genetic programming (GP) learning techniques are used in the models...
Spontaneous Combustion in Coal Seam (SCCS) is seriously threatening coal mine safety. A novel approach to predict SCCS by using Support Vector Machine (SVM) is present. The SVM is based on statistical learing theory with a simple structure and good generation properties. The basic SVM principle was firstly reviewed. Then, the kernel function was choiced, and the model parameters were optimized with...
In this paper the problem of prediction of queue lengths in the multi-queue-single-processor queuing system is considered. Efficient solutions for this problem are crucial in many technical appliances, such as load balancing in multi-processor systems. Here, a fuzzy-neural model for approximation of the average future system load along with model identification algorithm are proposed. Moreover, condition...
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