This paper is an attempt to estimate the quantity of Industrial solid waste (ISW) that can be generated in the Durg-Bhilai Twin city (DBTC), C.G, India from 2010 to 2026. The prediction of Industrial solid waste generation plays an important role in solid waste management. Yet achieving the anticipated prediction accuracy with regard to the generation trends facing many fast growing regions is ...

The conventional method for determining the Marshall Stability (MS) and Flow (MF) of asphalt pavements entails laborious, time-consuming, expensive laboratory procedures. In order to develop new advanced prediction models MS MF current study applied three soft computing techniques: Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Multi Expression Programming (MEP)...

Forecasting energy price and consumption is essential in making effective managerial decisions and plans. While there are many sophisticated mathematical methods developed so far to forecast, some nature-based intelligent algorithms with desired characteristics have been developed recently. The main objective of this research is short term forecasting of energy price and consumption in Iranian ...

The systemic nature of the risk bankruptcy financial institutions has become an important issue in maintaining existence and stability domestic global finance. use statistics for prediction so far provides optimal benefits. However, this approach limitations, especially since model is built based on systematic relationships, linearity normality aspects are often weaknesses. This can be overcome...

Forecasting the compressive strength of concrete is a complex task owing to interactions among ingredients. In addition, an important characteristic failure surface its six-fold symmetry. this study, artificial neural network (ANN) and adaptive neuro fuzzy interface system (ANFIS) were employed model natural volcanic ash mortar (VAM) by using symmetry failure. The modeling was correlated with f...

This article presents a comparison between two types of intelligent models: Artificial Neural Networks ANN and Adaptative Neuro-Fuzzy Interference System ANFIS, for forecasting flows in a section of Bogotá (Colombia) river, looking for the most efficient. The simulation was performed in the Matlab computer software, with data collected by hydrological stations of the Corporación Autónoma Region...

Abstract In a flood-prone region, quick and accurate flood forecasting is imperative. It can extend the lead time for issuing disaster warnings and allow sufficient time for habitants in hazardous areas to take appropriate action, such as evacuation. In this paper, two hybrid models based on recent artificial intelligence technology, namely, genetic algorithm-based artificial neural network (AN...