Logopedics is special pedagogical subject that deals with the prevention and correction of speech defects. Logopedics as a science was formed out of practical and theoretical reasons, extending its area from the language and communication research in relation to the evolution of personality to that of the formulation of laws and methods of language correction, the presentation of verbal difficulties, and verbal behavior stimulation. Speech disorders are determined by a range of causes that act isolated or associated, this is why the causes must be thoroughly known, as to establish the diagnosis and find the best therapeutic intervention methods. There is an increasing number of children with speech disorders in kindergarten environment. An experiment was conducted to observe the difficulties teachers face. A group of 20 children (8 girls and 12 boys) was used for a period of 4 months on whom questionnaires to correct language disorders were applied.
The transmission network expansion planning (TNEP) problem is tackled within this paper. The TNEP study is approached for a real power system designed based on the Western and South-Western parts of the Romanian Power System. The study is performed considering 3 consumed power evolution scenarios and power transfers. The complete a.c. power flow computing mathematical model has been applied. To solve this problem the particle swarm optimization (PSO) technique (artificial intelligence field) is used. Few practical considerations are presented, followed by the developed software tool. The results are discussed in details for one case and for the other two cases, they are summarized. Keywords-power system; mathematical model; software tool; (auto)transformer; overhead line; expansion planning; optimizationI. INTRODUCTION Garver in [1] has proposed the use of linear programming technique for TNEP solving. The initial data have been represented by: power system configuration, consumed power forecast and real power sources' evolution plan. The power flow is computed and new lines are introduced, having as a goal to avoid power system branches overloading. The optimization problem is solved using linear programming techniques. Such an approach has the following drawbacks: a linear mathematical model is used for power flow computing, reactive power flow is not tackled, real power losses are neglected, objective function (OBF) refers to the power system branch overloading cost minimization, etc.[2].In [3] it is stipulated that the TNEP is a mixed nonlinear optimization problem, with real and integer variables. In [4] the real power losses are approximately considered. Also, the OBF is extended referring to the total cost minimization formed by investment cost (related to the transmission network expansion) and generating units operation cost. These type of problems are solved in [5] applying a meta-heuristic technique for exploring the solution space. In [6] an additional term is added to the OBF expression, taking into consideration aspects related to the power system safety operation. It is computed based on several N-1 criterion operating conditions. TNEP is approached from the linear integer programming point of view in [7]. A "branch and bound" type algorithm is applied. To control the power system expansion candidate set the algorithm is trained based on a knowledge data-base. The inappropriate solutions are avoided imposing inferior and superior OBF limits.Currently, the (meta)heuristic methods are largely applied for optimization problems solving. In case of TNEP, these techniques are applied to generate possible solutions, to evaluate them and to select the most appropriate ones. The algorithm
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