An outdoor crop-bed was prepared to observe scatterometer response in the angular range of 20◦ to 70◦ at VVand HHpolarization. The soil moisture and crop variables like plant height, leaf area index and biomass of crop ladyfinger were measured at different growth stages of the crop ladyfinger. Temporal variation in scattering coefficient was found highly dependent on crop variables and observed...

hammerstein-wiener (hw) models are capable in describing nonlinear dynamic systems. these models are nonlinear and have been widely used in a wide range of sciences due to their simplicity and having a physically-based concept. in this research, for the first time in hydrology and water resources management, three different structures of these models using daily temperature and precipitation da...

an artificial neural network has been used to determine the volume flux and rejections of ca2+ , na+ and cl¯, as a function of transmembrane pressure and concentrations of ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. the feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidden la...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

The problematic and undesirable effects of weeds lead to degradation in the quality productivity yields. These unacceptable are close competitors crops as they constantly devour water, air, nutrients, sunlight which helpful for maturation crops. For better cultivation good production crops, weed detection at appropriate time is an essential stride. In recent years, various state-of-the-art (SOT...

Crop yield forecasting mainly focus on the domain of agriculture research which has a great impact making decisions like import-export, pricing and distribution respective crops. Accurate predictions with well timed forecasts is very important tremendously challenging task due to numerous complex factors. Mainly crops wheat, rice, peas, pulses, sugarcane, tea, cotton, green houses etc. can be u...

in this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and newton-cotesmethods with positive coefficient for the solution of linear fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. here neural network isconsidered as a part of large field called neural computing orsoft computing. we propose alearning algorithm from ...

production of highly viscous tar sand bitumen using steam assisted gravity drainage (sagd) with a pair of horizontal wells has advantages over conventional steam flooding. this paper explores the use of artificial neural networks (anns) as an alternative to the traditional sagd simulation approach. feed forward, multi-layered neural network meta-models are trained through the back-error-propaga...

Deep learning is a cutting-edge image processing method that still relatively new but produces reliable results. Leaf disease detection and categorization employ variety of deep approaches. Tomatoes are one the most popular vegetables can be found in every kitchen various forms, no matter cuisine. After potato sweet potato, it third widely produced crop. The second-largest tomato grower world I...