The aim of this research is to develop a farmer prediction system to identify crop suitable for particular soil. To achieve this Neural Network should be trained to perform correct prediction for farmers. After the network has been properly trained, it can be used to identify the crop suitable for particular type of soil. The Artificial neural networks are relatively crude electronic networks o...

the aim of this study is quantity determining and evaluating of the quality position of teaching and learningprocess. so, the artificial neural networks were used for modeling nonlinear relationships to inspect and evaluate different models of service quality evaluation. the statistical population include 1070 peoples, which were master and phd students of faculty of agriculture of ferdowsiuniv...

high processing loads, need for complicated and frequent updating, and high false alarm are some of the challenges in designing anomaly detection and misuse detection systems. we propose a new network-based intrusion detection system (ids) that resolves such shortcomings. our scheme fuses anomaly detection and misuse detection systems, which has not been utilized so far in existing systems. in ...

there is little consensus on the corporate diversification-efficiency relationship in the diversification literature. according to the corporate diversification, firms have a tendency to get more market share with diversifying in the local segment or in the international market. theoretically, a contradictory exists between the profitable strategy and the value reducing strategy in the diversif...

over the last decade or so, artificial neural networks (anns) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. however, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. for this reason, this study aims at de...

the successful key of trading in the forex market is the selection of correct exchange in proper time based on an exact prediction of future exchange rate. foreign exchange rates are affected by many correlated economic, political and even psychological factors. therefore, in order to achieve a profitable trade these factors should be considered. the application of intelligent techniques for fo...

During the past few years, modeling in agriculture has attracted considerable attention. New modeling methods including neural networks are employed in various industries, and it is necessary that their use in agriculture be also considered. This research addressed the trend of energy use in broiler farms in Alborz Province and sought to model the trend of energy consumption and production in t...

This paper presents a review of applications of artificial neural networks in biomedical engineering area. Artificial neural networks in general are explained; some limitations and some proven benefits of neural networks are discussed. Use of art ificial neural network techniques in various biomedical engineering applications is summarised. A case study is used to demonstrate the efficacy of ar...

The authors have been developing several models based on artificial neural networks, linear regression models, BoxJenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels” of one region. Several comparisons between the different type models have been experimented as well as the features used at the e...

An integrated Artificial Neural NetworkParticle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world’s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World’s population, Gross domestic product (GDP), o...