the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

p2x 7 antagonist activity for a set of 49 molecules of the p2x 7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. the activity of these compounds was estimated by means of combination of principal component analysis (pca), as a well-known data reduction method, genetic algorithm (ga), as a variable selection technique, ...

The creation process of Artificial Neural Networks (ANNs) used to be quite slow and the human expert had to test several architectures until finding the one that achieves the best results for the solution of a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically creating ANNs. This technique also allows the obtaining of simplified networks wit...

to determine the amount of food amino acid and to spend time in the laboratories are expensive & time-consuming due to a chemical analysis. in the current laboratories, digestion nirs method is widely used for this purpose. but this method has technical limitation. therefor is important find appropriate method for estimate amount of amino acids. artificial neural network (ann) can provide a bet...

the present investigation entails a procedure by which the surface tension and viscosity of liquids could be redicted.to this end, capillary experiments were performed for porous media by utilizing fifteen different liquids and powders. the time of capillary rise to a certain known height of each liquid in a particular powder was recorded. two artificial neural networks (anns) were designed and...

Coagulation process is an essential part of drinking water treatment operations. The jar test is a widely-used laboratory procedure to determine the quantity of coagulation chemical dosages for water treatment plants. However, the test is not effective for real-time control of this process due to the nonlinear behaviour and rapid variations of water quality parameters. In this study, empirical ...

In this paper, a nonlinear symbolic regression technique using an evolutionary algorithm known as multi-gene genetic programming (MGGP) is applied for a data-driven modelling between the dependent and the independent variables. The technique is applied for modelling the measured global solar irradiation and validated through numerical simulations. The proposed modelling technique shows improved...

This study applies four different types of machine learning methods to model the power performance behaviour of a tubular solid oxide fuel cells (SOFC) under different operating conditions. The corresponding machine learning methods are: artificial neural network (ANN), fuzzy inference system (FIS), support vector machine (SVM), and genetic programming (GP). By using four types of inputs of the...

This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of ne...