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...

job satisfaction (js) plays important role as a competitive advantage in organizations especially in helth industry. recruitment and retention of human resources are persistent problems associated with this field. most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. however, little researchs have focused on the ...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

profitability as the most important factor in decision-making, has always been considered by stake­holders in the company&apos;s profitability. also can be a basis for evaluating the performance of the managers. the ability to predict the profitability can be very useful to help decision-makers. that&apos;s why one of the most important issues is the expected profitability. the importance of th...

facts technology has considerable applications in power systems, such as; improving the steady stateperformance, damping the power system oscillations, controlling the power flow, and etc. statcom is oneof the most important facts devices used in the parallel compensation, enhancing transient stability andetc. since three phase fault is widespread in power systems, in this paper statcom is used...

In this paper, a reliability approach on reconfiguration decisions in a supply chain network is studied based on coupling the simulation concepts and artificial neural network. In other words, due to the limited budget for warehouse relocation in a supply chain, the failure probability is assessed for determining the robust decision for future supply chain configuration. Traditional solving ...

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.

Introduction: Hypothyroidism is one of the frequent side effects of radiotherapy of head and neck cancers, breast cancer, and Hodgkin's lymphoma. It is recommended to estimate the normal tissue complication probability of thyroid gland using radiobiological modeling during treatment planning. Moreover, the use of artificial neural network is also proposed as a new method for t...

objective(s): this study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ann) and correlation using experimental data. methods: two-layer perceptron feedforward artificial neural network and backpropagation levenberg-marquardt (bp-lm) training algorithm are used to predict the thermal cond...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...