A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i

Solar tracking systems used are to increase the efficiency of the solar cells have attracted the attention of
researchers recently due to the fact that the attention has been directed to the renewable energy sources. Solar tracking systems are of two types, Maximum Power Point Tracking (MPPT) and sun path tracking. Both types are studied briefly in this paper and a simple low cost sun path tracking system is designed using simple commercially available component. Measurements have been made for comparison between fixed and tracking system. The results have shown that the tracking system is effective in the sense of relatively high output power increase and low cost.

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

The wake potential and wake phenomena for swift proton in an amorphous carbon target were studied by utilising various dielectric function formalisms, including the Drude dielectric function, the Drude–Lorentz dielectric function and quantum dielectric function. The Drude model results exhibited a damped oscillatory behaviour in the longitudinal direction behind the projectile; the pattern of these oscillations decreases exponentially in the transverse direction. In addition, the wake potential extends slightly ahead of the projectile which also depends on the proton coordinate and velocity. The effect of electron binding on the wake potential, characterised by the ratio to 0.1, has been studied alongside the Drude–Lorentz dielectric

Mobile ad hoc network is nothing but the temporary network which is having the collection of mobile nodes. Routing and broadcasting are major operations of MANET network. The major operation in ad hoc mobile network is the broadcasting which sometime results to storm problem of the broadcast if the forwarding mechanism is not properly designated. Thus the challenges in the MANET are to reduce the broadcasting redundancy and under high transmission error rate provides high delivery ratio. Hence in our proposed research, we are introducing and investigating the new mechanism of broadcasting called Dual Covered Broadcast. This method takes the broadcast redundancy advantage order to improve packet delivery ratio especially under environments w

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i