this study shows the usefulness of artificial neural network (ann) in maintenance planning and man-agement. an ann model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. the model achieved an accuracy of over 70% in predicting the expected downtime.

rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. among these models, the artificial neural network (ann) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. in addition,anns are quick and flexible approaches which provide very ...

in recent years, biodiesel has been considered as a good alternative of diesel fuels. density and viscosity are two important properties of these fuels. in this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ann). a three-layer feed forward neural network with levenberg-marquard (lm) algorithm was used for learning empirical ...

background and aims: depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. so, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. use of this memory is latent in synthetic neuro-fuzzy algorithm. present article in...

twenty four cowpea varieties were raised at niab and arri, faisalabad selected for plant height (42-136cm) days taken to 95 % flowering (62-79 days) and for diseases resistance (0.67-7 rating). infestation was maximum on it-97k-461-4, 1068-7, it-97k 1042-8 and it-98k-558-1 and was graded as susceptible. maximum grain yield was recorded in elite (649 kg/ha) and lowest grain yield was observed in...

accurate prediction of municipal solid waste’s quality and quantity is crucial for designing and programming municipal solid waste management system. but predicting the amount of generated waste is difficult task because various parameters affect it and its fluctuation is high. in this research with application of feed forward artificial neural network, an appropriate model for predicting the...

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 ...

abstract: in this study the reliability of using response surface-neural network method to predict the osmotic dehydration properties of crookneck squash has been investigated. in order to carry out this project, the osmotic solution concentration, the osmotic solution temperature and immersion time were chosen as inputs and solid gain and water loss were selected as outputs of the designed net...

background: the artificial neural networks (anns) are useful in solving nonlinear processes, without the need for mathematical models of the parameters. since the relationship between the ct numbers and material compositions is not linear, ann can be used for obtaining tissue density and composition. objective: the aim of this study is to utilize ann for determination of the composition and mas...

background & aims of the study: a feed forward artificial neural network (ffann) was developed to predict the efficiency of total petroleum hydrocarbon (tph) removal from a contaminated soil, using soil washing process with tween 80. the main objective of this study was to assess the performance of developed ffann model for the estimation of   tph removal. materials and methods: several indepen...