Water Quality plays an important role in attaining a sustainable aquaculture system, its cumulative effect can make or mar the entire system. The amount of dissolved oxygen (DO) alongside other parameters such as temperature, pH, alkalinity and conductivity are often used to estimate the water quality index (WQI) in aquaculture. There exist different approaches for the estimation of the quality...

ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (anns) are introduced to obtain improved regional low-flow estimates at ungauged sites. a multilayer perceptron (mlp) network is used to identify the funct...

abstract from longley, the various equations for determining the runoff to water management are presented by the researchers that are widely used in hydrologic sciences. in this study by using observational data, was evaluated empirical, artificial neural network (ann) and ca-active neuro-fuzzy inference system (canfis) models in estimation of runoff. for this purpose, by using climatic and phy...

Nowadays 90% of the required water of Iran is secured with groundwater resources and forecasting of pollutants content in these resources is vital. Therefore, this research aimed to develop and employ the feedforward artificial neural network (ANN) to forecast the arsenic (As), lead (Pb), and zinc (Zn) concentration in groundwater resources of Asadabad plain. In this research, the ANN models we...

this study presents the effects of project uncertainties on nonlinear time-cost tradeoff (tct) profile of real life engineering projects by the fusion of fuzzy logic and artificial neural network (ann) models with hybrid meta-heuristic (hmh) technique, abridged as fuzzy-ann-hmh. nonlinear time-cost relationship of project activities is dealt with ann models. ann models are then integrated with ...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

in order to comparing geostatistics and artificial neural networks (ann) methods in predicting soil salinity and clay content this experiment was conducted in sistan region land. 121 soil samples were taken at the depth of 0-30 cm within the grid of 750 750 m and soil ec and clay percent were determined. 105 samples were used for training and 16 samples were used for test in both models. diffe...

This study presents the effects of project uncertainties on nonlinear time-cost tradeoff (TCT) profile of real life engineering projects by the fusion of fuzzy logic and artificial neural network (ANN) models with hybrid meta-heuristic (HMH) technique, abridged as Fuzzy-ANN-HMH. Nonlinear time-cost relationship of project activities is dealt with ANN models. ANN models are then integrated with ...

simulation of groundwater fluctuations plays a crucial role in management of watersheds and water demand balancing. recently, wavelet analysis has been used widely in time series decomposition and coupling with neural networks for hydrological modeling. in this paper, the ability of the wavelet-dynamic artificial neural networks (w-ann) model was applied in forecasting one-month-ahead of ground...