Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

The relationship between stock size and recruitment is an essential element in the understanding of the productivity of a population. However, predicting the number of recruits produced by a population has proven to be a difficult challenge. This may in part be a result of poor estimation of reproductive potential (RP). We determined if including increased information on reproductive biology in...

The quality higher education is required for growth and development of country. Professional education is one of the pillars of higher education. Data mining techniques aim to discover hidden knowledge in existing educational data, predict future trends and use it for betterment of higher educational institutes as well as students. The objective of this study is to use prediction technique usin...

The CENTROIDFOLD web server (http://www.ncrna.org/centroidfold/) is a web application for RNA secondary structure prediction powered by one of the most accurate prediction engine. The server accepts two kinds of sequence data: a single RNA sequence and a multiple alignment of RNA sequences. It responses with a prediction result shown as a popular base-pair notation and a graph representation. P...

Battery SOC is acted as an essential parameter for EV and HEV, its accurate estimate relates to whether the vehicle control strategy is implemented correctly. There has been no other prediction method, which can obtain a more accurate prediction result. To overcome this deficiency, this paper presents a method to build a battery SOC estimation models using principal component analysis (PCA). PC...

Prediction of solar irradiance has great significance to photovoltaic power forecasting and the scheduling plan of power generation. Aim at unsatisfactory prediction accuracy of traditional forecasting methods, this paper presents an approach to predict solar irradiance of photovoltaic power station based on wavelet decomposition and extreme learning machine. With historical irradiance sequence...

The following paper presents the use of regularized linear models as tools to optimize training process. The models were calculated by using data collected from race-walkers’ training events. The models used predict the outcomes over a 3 km race and following a prescribed training plan. The material included a total of 122 training patterns made by 21 players. The methods of analysis include: c...