Abstract
Neural networks have broad applicability to real power system problems. One of the areas in power system with huge interest in appliance of neural networks is load forecasting. In this paper the neural networks were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 44 day period. The artificial neural networks showed as a good nonlinear approximator, giving promising results. The main objective of the presented work is to interest power companies in the Region for possible practical implementations.

Abstract

Abstract
This paper is written with the didactic purpose of exploring and indicating possibilities to power companies in the Balkan region for the application of adaptive neuro-fuzzy inference system (ANFIS) models in load prediction with real load data set. ANFIS models were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 42 day period. Simulation results gave promising results especially considering small size of used data set. Although the objective of the paper is to demonstrate possibilities for practical implementation, further research and improvement including the contributions of similar approaches in the world must he done.

Abstract
This paper studies periodic gaits of quadruped locomotion systems. The purpose is to determine the best set of gait and locomotion variables during walking, for different robot velocities, based on two formulated performance measures. A set of experiments reveals the influence of the gait and locomotion variables upon the proposed indices, namely that the gait and the locomotion parameters should be adapted to the robot forward velocity.

Abstract
The text explains that the fuzzy approaches have the objective to bring the decision process in planning closer to the decision maker, by allowing him to understand better the diversity of aspects that must be considered in planning decisions and helping the decision process while keeping, as much information as possible, represented in the definition of fuzzy sets. The paper shows that the qualitative aspects of uncertainty, risk and decision making may be adequately modeled with a fuzzy set approach. It could help the decision maker guiding him towards a decision that takes in account uncertainty in the future, the multiple criteria evaluation of plans, as well as hedging policies.

Abstract
This work presents a model developed to evaluate the Dynamic Adaptation of an Electric Energy Distribution System (EEDS) respect to its planning for a given period of Tariff Control. The model is based on a two-stage strategy that deals with the mid/short-term and long-term planning, respectively. The starting point for modeling is brought about by the results from a multi-attribute method based on Fuzzy Dynamic Programming and on Analytic Hierarchy Processes (FDP + AHP) for a mid/short-term horizon. Such a method produces a set of possible evolution trajectories which can be defined as satisfactory when they evolve above a given risk threshold that the planner is willing to accept. Then, the decision-making activities within the framework of the Analytical Hierarchy Processes are those tasks that allow defining a vector for dynamic adaptation of the system, which is directly associated to an eventual series of imbalances that take place during its evolution.