Neural networks (NN) have demonstrated to be useful for estimating software development effort. A NN can be classified depending of its architecture. A Feedforward neural network (FFNN) and a General Regression Neural Network (GRNN) have two kinds of architectures. A FFNN uses randomization to be trained, whereas a GRNN uses a spread parameter to the same goal. Randomization as well as the spre...

Permeability is a key parameter associated with the characterization of any hydrocarbon reservoir. In fact, it is not possible to have accurate solutions to many petroleum engineering problems without having accurate permeability value. The conventional methods for permeability determination are core analysis and well test techniques. These methods are very expensive and time consuming. Therefo...

9-nitrocamptothecin (9-nc) is a semisynthetic and a low soluble analogue of camptothecin alkaloids that target nuclear enzyme topoisomerase i. the unstable lactone form of 9-nc in biological fluids requires for its cytotoxic activity. to improve aqueous solubility and stability in biological media, 9-nc was loaded in polymeric nanoparticles. in this paper, we studied the effect of peg percent (...

Wind speed forecast is essential in wind energy conversion system and may fail to operate power plant at non optimal region if not properly forecasted. This paper focuses the short term wind speed forecasting using conventional statistical method and artificial neural networks such as back propagation network (BPN), generalized regression neural network (GRNN) and radial basis function networks...

In this work, some ubiquitous neural networks are applied to model the landscape of a known problem function approximation. The performance of the various neural networks is analyzed and validated via some well-known benchmark problems as target functions, such as Sphere, Rastrigin, and Griewank functions. The experimental results show that among the three neural networks tested, Radial Basis F...

Recently, neural network based sentence modeling methods have achieved great progress. Among these methods, the recursive neural networks (RecNNs) can effectively model the combination of the words in sentence. However, RecNNs need a given external topological structure, like syntactic tree. In this paper, we propose a gated recursive neural network (GRNN) to model sentences, which employs a fu...

Multi-objective optimization can help identify efficient and appealing designs of urban drainage systems. However, their application to large-scale problems is hindered by the computational cost simulation. We propose a novel disaggregation approach that allows simulating portion network while remaining part represented surrogate model maps changes in region interest hydraulic head time-series ...

In this paper, a new aerodynamic solution strategy for non-smooth configurations is proposed based on the wall modification model by machine learning to perform numerical simulations, rather than directly describing global flow field with massive grids. The effect of in presence pressure gradients investigated utilizing method. Flow features surface are provided high-fidelity data acquired thro...

In today's global economy, accuracy in predicting the foreign exchange rate or at least trend correctly is of crucial importance for any future investment and this mostly achieved by use computational intelligence-based techniques as explored paper. The aim study was to develop an Artificial Neural Network (ANN) Model GHS/USD with inflation, nominal growth, monetary policy, interest rate, trade...

The real-time pose measurement of parallel robot helps to achieve the closed loop pose control and improve the control and operating performance of parallel robot. But it is difficult to implement the realtime pose measurement directly. In order to solve the pose measurement problem of a 6-DOF parallel robot, the kinematics analysis of the parallel robot is made, and a Generalized Regression Ne...