نتایج جستجو برای: model prediction
تعداد نتایج: 2268517 فیلتر نتایج به سال:
Background and Objectives: Considering the importance of safety evaluation of fish and seafood from capture to purchase, rapid and nondestructive methods are in urgent need for seafood industry. This study aimed to assess the application of hyperspectral imaging (HSI: 430-1010 nm) for prediction of total volatile basic nitrogen (TVB-N) in Japanese-threadfin bream (Nemipterusjaponicus) fillets, ...
the decisions made in the planning phase of a building project greatly affect its future operation and maintenance (o&m;) cost. recognizing the o&m; cost of condominiums’ common facilities as a critical issue for home owners, this research aims to develop an artificial neural network (ann) o&m; cost prediction model to assist developers and architects in effectively assessing the impacts of the...
Abstract Background: There is no reliable prediction model on the rate of mortality due to road traffic accidents in Iran. The present study aimed to predict deaths from road traffic crashes in Iran. Materials and methods: All death records from traffic accidents in Iran between March 2004 and March 2011 were analyzed. The Box-Jenkins time series model was used for obtaining trends. Death f...
Enhanced oil recovery using nitrogen injection is a commonly applied method for pressure maintenance in conventional reservoirs. Numerical simulations can be practiced for the prediction of a reservoir performance in the course of injection process; however, a detailed simulation might take up enormous computer processing time. In such cases, a simple statistical model may be a good approach to...
Optimal crop water requirement is needed for precise irrigation scheduling. Prediction of crop water requirements is a basic factor to achieve this goal. In this study, maize potential evapotranspiration (ETp) was prediced by maize simulation model (MSM). Then, it was evaluated and validated using experimental field data obtained in Agricultural Research Station of Shiraz University (Bajghah, F...
Dynamic Bayesian network is the extension of Bayesian network in solving time series problems .It can be well dealt with the time-varying multivariable problem. A state model is given based on Dynamic Bayesian network. The model can more accurately describe the relationship between the system state and the influencing factors. Single-step and multi-step prediction algorithms are given to predic...
The artificial neural networks (ANN) are the learning algorithms and mathematical models, which mimic the information processing ability of human brain and can be used to non linear and complex data. The aim of this study was to compare artificial neural network and regression models for prediction of body weight in Raini Cashmere goat. The data of 1389 goats for body weight, height at withers ...
in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...
Nowadays operational research has become a part of financial re-search. One way that operational research can be used in financial re-search is designing financial distress prediction models. In this re-search we designed a financial distress prediction model based on lo-gistic regression and on financial ratios and efficiency scores. For this purpose, we designed and tested two models: 1- fina...
This study presents a novel intelligent Fuzzy Genetic Differential Evolutionary model for the optimization of a fuzzy expert system applied to heart disease prediction in order to reduce the risk of heart disease. To this end, a fuzzy expert system has been proposed for the prediction of heart disease. The proposed model can be used as a tool to assist physicians. In order to: (1) tune the para...
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