Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO.

This paper proposed an adaptive A* Hybrid algorithm combining the advantages of ant colony and A* algorithm. Improvements of the traditional ant-colony algorithm was suggested, and the Target Evaluation Factor based on global dynamic information was introduced to promote the performance of ant path decision. In additional, an adaptive pheromone updating strategy was designed to balance and speed up the convergence rate. Test results showed that this algorithm can effectively guide agents to get an optimal path to ensure the efficient completion of tasks.

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Abstract. The output of photovoltaic array under uniform light is nonlinear with single peaks. Among the MPPT strategies, The P&O Maximum Power Point Tracking algorithm is mostly used, due to its ease of implementation. However, its main drawbacks are the waste of energy in steady conditions, when the working point moves across the MPPT and the poor dynamic performances exhibited when a step change in solar irradiance or in temperature occurs. Because of this disadvantage, P&O based on variable metric method is proposed. Combining these two algorithms, use variable metric can automatic change the step-size during the process. Compared with the conventional fixed step size method, the proposed approach can effectively improve the MPPT speed and accuracy simultaneously. A theoretical analysis and the design principle of the proposed algorithm are provided and its feasibility is also verified by simulation.

Since there are a variety of uncertainties and probabilities in the actual world, mathematicians and other researchers have found numerous answers to these common problems. They have also developed theories, such as the probability theory, to help them organize their significant discoveries. A drunk person will eventually find their way home, but a drunk bird might never find it, as said by Shizuo Kakutani. A random walk, in its most basic definition, is just a path on a network or lattice where each step is decided at random using some probability distribution, such a coin or fair dice. A motion, such as going left or right on a number line or up or down on a plane, would correspond to each outcome of tossing a coin, heads or tails. Recurrent random walks are those that end up back at the beginning after a predetermined number of steps. Any non-recurrent random walk is transitory.