A self adaptive probabilistic neural network model is proposed. The model incorporates the Particle Swarm Optimization algorithm to optimize the spread parameter of the probabilistic neural network, enhancing thus its performance. The proposed approach is tested on two data sets from the field of bioinformatics, with promising results. The performance of the proposed model is compared to probab...

In this contribution a new supervised classification model is proposed, namely the Fuzzy Evolutionary Probabilistic Neural Network (FEPNN). The proposed model incorporates a fuzzy class membership function into the recently proposed Evolutionary Probabilistic Neural Network (EPNN). EPNN employs an evolutionary algorithm, namely the Particle Swarm Optimization (PSO), for the selection of the spr...

In this paper, we present the mathematical foundations of a probabilistic neural network for gene selection and classification of high-dimensional microarray data. We present a catalogue of features that a classification system for microarray data should incorporate. We then use this catalogue and compare the theoretical properties of probabilistic neural networks with support vector machines w...

Two sources of weak biometric data are investigated for the development of user identification models. A probabilistic neural network model is created from keystroke digraph features extracted from raw typing data. A second model is developed from scan-path features extracted from raw eye-tracking data. A third model is created from a combination of features from the two biometric sources. Expe...

Understanding efficiency levels is crucial for understanding the competitive structure of a market and/or segments of a market. This study uses two artificial neural networks (NN) and a traditional statistical classification method to classify the relative efficiency of top listed Egyptian companies. Accuracy indices derived from the application of a non-parametric data envelopment analysis app...

Tujuan penelitian ini untuk mengklasifikasikan citra Songket Aceh. Data menggunakan sepuluh motif Aceh dan data diperoleh dari tempat usaha tenun Nyak Mu. Tahapan adalah akuisisi citra, pra-proses, ekstraksi fitur, klasifikasi evaluasi. Ekstraksi fitur tekstur metode Gray Level Co-occurrence Matrix (GLCM). Fitur-fitur yang digunakan pada entropy, energy, sum of squares: variance, difference ent...

in this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. in other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. first, an analytical approach is proposed to simplify the structure of network. then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (tfn). this paper com...