Energy is regarded as one of the most important elements in agricultural sector. During the last decades energy consumption in agriculture has increased, so finding the relationship between energy consumption and crop yields in agricultural production can help to achieve sustainable agriculture. In this study several adaptive neuro-fuzzy inference system (ANFIS) models were evaluated to predict...

Dryer system is a controlled plant which is normally used in chemical industry. The proper modeling of this system facilitates its maintenance and keeping. Normally this is not an easy task, unless having a complete model of the process, due to sudden and nonlinear events. In this paper the linear identification of dryer plant in Arak petroleum, is introduced according to the Autoregressive wit...

In this paper, both the architecture and learning procedure underlying the parallel layer perceptron is presented. This topology, di1erent to the previous ones, uses parallel layers of perceptrons to map nonlinear input–output relationships. Comparisons between the parallel layer perceptron, multi-layer perceptron and ANFIS are included and show the e1ectiveness of the proposed topology. c © 20...

the main objective in classification of the nmr spectra of cancerous and healthy tissue , with high number of features is the prerequisites of the minimum number of samples. therefore the use of conventional classifier on this type of the data is not recommended. in the current work, different structures of the artificial neural networks (ann) were tried on classification of different cancerous...

In case of decision making problems, identification nonlinear systems is an important issue. Identification using a multilayer perceptron (MLP) trained with back propagation becomes much complex increase in number input data, layers, nodes, and iterations computation. this paper, attempt has been made to use fuzzy MLP its learning algorithm for system. The training which allows accelerate proce...

* Professor Sungyoung Lee is the corresponding author. Abstract Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised learning or lacking of mechanisms to utilize some prior knowledge about data (semi-supervised learning) for improving clustering result. In an effort to archi...

N eural networks are very powerful as nonlinear signal processors, but obtained results are often far from satisfactory. The purpose of this article is to evaluate the reasons for these frustrations and show how to make these neural networks successful. The following are the main challenges of neural network applications: 1) Which neural network architectures should be used? 2) How large should...

Several neural network architectures have been developed over the past several years. One of the most popular and most powerful architectures is the multilayer perceptron. This architecture will be described in detail and recent advances in training of the multilayer perceptron will be presented. Multilayer perceptrons are trained using various techniques. For years the most used training metho...

Accurate disease diagnosis and proper management is a matter of concern to everybody. In this context, there are a number of uncertainties involved including human errors. The problem is augmented when the domain is itself critical; for example, neonatal diseases. The problem is further augmented whenever and wherever proper experts are not available. Mitigating the kind of such problems, devel...

Classification of heart sound signals to normal or their classes of disease are very important in screening and diagnosis system since various applications and devices that fulfilling this purpose are rapidly design and developed these days. This paper states and alternative method in improving classification accuracy of heart sound signals. Standard and improvised Multi-Layer Perceptron (MLP) ...