The study of drought and its forecasting plays an important role in planning managing water resource systems, especially extreme climatic periods. This aims to analyze forecast characteristics, through the use Reconnaissance Drought Index (RDI) order temporal spatiotemporal nine climate stations Kurdistan Region Iraq for period (1973-2020) detect beginning end period, as well future droughts us...

Feed-forward Artificial Neural Networks (ANNs) have become popular among researchers and practitioners for modelling complex real–world problems. One of the latest research areas in this field is evolving ANNs. In this paper, we investigate the simultaneous evolution of architectures and connection weights in ANNs. In simultaneous evolution, we use the concept of multiobjective optimization and...

improving time series forecastingaccuracy is an important yet often difficult task.both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. in this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

Cryptography is the ability of changing information into obvious unintelligibility in a way allowing a secret method of un-mangling. The vital idea of cryptography is the capability to send information between participants in a way that prevents others from reading it. Much cryptography methods are available which are based on number theory but it has the disadvantage of requirement a large com...

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpos...

This paper describes the time variant changes in satellite images using Self Organizing Feature Map (SOFM) technique associated with Artificial Neural Network. In this paper, we take a satellite image and find the time variant changes using above technique with the help of MATLAB. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main co...

The aim of this paper is to rank the impact of Object Oriented(OO) metrics in fault prediction modeling using Artificial Neural Networks(ANNs). Past studies on empirical validation of object oriented metrics as fault predictors using ANNs have focused on the predictive quality of neural networks versus standard statistical techniques. In this empirical study we turn our attention to the capabil...

In recent years, due to the powerful abilities to deal with highly complex tasks, the artificial neural networks (ANNs) have been studied in the hope of achieving human-like performance in many applications. Since the ANNs have the ability to approximate complex functions from observations, it is straightforward to consider the ANNs for steganography. In this paper, we aim to implement the well...

Estimate of sediment load is required in a wide spectrum of water resources engineering problems. The nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods to simulate the suspended sediment load. In this study Artificial Neural Networks (ANNs) are employed to estimate daily suspended sediment load. Two different ANN algorithms, Multi Layer Perce...