A method of establishing a prediction model the greenhouse temperature based on time-series analysis and boosting tree is proposed, aiming at problem that cannot be accurately predicted owing to nonlinear changes in closed ecosystem featuring modern agricultural technology various influencing factors. This comprehensively considers environmental parameters, including humidity inside outside gre...

fuzzy time series have been developed during the last decade to improve the forecast accuracy. many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. in this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly effici...

water quality is a worldwide problem which affects human beings lives fundamentally. water scarcity is intensified in result of quality deterioration. different factors such as population increase, economic development and water pollution could be considered as the origins of the problem. the study and forecasting of water quality is necessary to prevent serious water quality deteriorations in ...

this paper presents the prediction of vehicle's velocity time series using neural networks. for this purpose, driving data is firstly collected in real world traffic conditions in the city of tehran using advance vehicle location devices installed on private cars. a multi-layer perceptron network is then designed for driving time series forecasting. in addition, the results of this study a...

In this study, the air temperature data obtained from “State Meteorological Service”, including 58 stations in Turkey for a period of 45 years between 19501994, was investigated. By using the yearly average temperatures, temperature time series were formed for mean temperatures for 58 stations. Gaussian smoothing, Mann-Kendall rank correlation and Wald-Wolfowitz serial correlation tests were ap...