Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Estimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

The aim of the research is to know the effect of a training program based on interactive teaching strategies on achievement and creative problem solving among fourth-grade students in chemistry of the directorate of education Rusafa first, the sample was divided into two groups, one experimental and numbering (29) students and the other control group numbering (30) students. The experimental group underwent the training program in the first semester of the year (2021-2022) and the control one studied according to the usual method. Two tools were built, the first being an academic achievement test consisting of (40) multiple-choice items, and the second a test of creative problem-solving skills in a chemistry subject and consisting o

In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the