A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic

<p>Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.</p><p>There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.</p><p>In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.</p>

Analytical Modeling of Solar Cells

<p>In the present work, a modified method is utilized to find the real roots of nonlinear equations of a single-diode PV cell by combining the modified Aitken's extrapolation method (MAEM), Aitken's extrapolation method (AEM) and the Newton-Raphson method (NRM), describing, and comparing them. The extrapolation method (MAEM) and (AEM) in the form of Aitken –acceleration is applied for improvement the convergence of the iterative method (Newton-Raphson) technique. Using a new improve to Aitken technique on (NRM) enables one to obtain efficiently the numerical solution of the single-diode solar cell nonlinear equation. The speed of the proposed method is compared with two other methods by means of various values of load resistance (R) in the range between R ∈ [1, 5] and with the given voltage of the cell as an initial value in ambient temperature. The results showed that the proposed method (MAEM) is faster than the other methods (AEM and NRM).</p>

Bernoulli Collocation Polynomials Algorithm for Calculus of Variational Problems

<p>This paper presents an approximate method that depends on the Bernoulli Polynomials as basic functions. The method is concerned with collocation technique for solving problems in calculus of variation. Some interesting properties of Bernoulli polynomials are used to reduce the original problem to mathematical problem. Some illustrative examples are described to show the applicability of the proposed method.</p>

Measuring the Solar Cell Parameters Using Fuzzy Set Technique

<p>This work studies the application of fuzzy set (FS) and fuzzy logic (FC) methods to determine the optimal operating point of solar cell. The physical parameters of the solar cell have been measured practically using silicon solar cell. The important parameters of the silicon cell are compared with each other using fuzzy set comparison method (FSCM) based on (I-V) characteristic curves of the voltage of photovoltaic cell and the maximum power resulting from the cell; which is a simple method for the measurement. The results of the simulation method show that, the fuzzy set comparison method (FSCM) is better measuring these parameters.</p>

Linear Programming for Solving Solar Cell Parameters

<p>In this paper, the major physical parameters of a commercial silicon solar cell such as maximum current, maximum voltage, fill factor, and efficiency have been investigated. The important parameters of a silicon cell are examined using Linear Programming Problem (LPB) and the obtained results are compared with those of experimental values. The experimental results of the solar cell show excellent agreement as compared with those obtained by LPB. </p>

Investigation of Solar Cell Factors using Fuzzy Set Technique

<p>Fuzzy set technique has been used to demonstrate the physical factors of a silicon solar cell. The physical parameters of a solar cell are calculated experimentally in outdoor measurement and the obtained values are compared with those obtained theoretically. The comparison results showed a good agreement using these two methods.</p>

Effect of Silicon Solar Cell Physical Factors on Maximum Conversion Efficiency Theoretically and Experimentally

<p>In this paper, ten major physical factors of a commercial silicon solar cell such as maximum current density, maximum voltage, maximum resistance, fill factor, energy conversion efficiency, life time , series and shunt resistances have been demonstrated. Integer linear programming (ILP) tests these factors of a commercial cell and the obtained results are compared with those of experimental values. The experimental results of the solar cell indicate excellent agreement as compared with those obtained by (ILP). </p>