An important problem in nonlinear science is estimation of unknown parameters in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of meta-heuristics. BA tries to model natural behavior of honey Bees in food foraging. This paper focuses on using the BA to solve this problem. Simulation results demonstrate the merit, effectiveness and robustness of BA.

Solar radiation estimation is integral part for various solar energy systems which requires precise and expensive devices to gage the solar radiation for a particular region. However, researches haveproposed different techniques to estimate the solar radiation that hinder using such devices so far.Nonlinear nature and excessive dependence on the meteorological parameters of these methods forced researchers to look for quick and efficient techniques to solve related issues and find solar radiation for a particular region. In this paper, a new method based on the Angstrom model is introduced which estimates the monthly average daily global solar radiation on a horizontal surface by Bees algorithm as a heuristic and population-based search technique implemented in MATLAB software. The experimental coefficients for Angstrom model are calculated for six different climate regions of Iran using proposed program written in the software. The obtained results proved the efficiency and predominance of the new method to find a more accurate level of solar radiation.

In the present study, the hydraulic-thermal design and optimization of a gasketed-plate heat exchanger (GPHE) with an objective function of heat exchanger performance index (the amount of transferred heat exchange to pumping power ratio) is carried out. This process is made by considering 6 design parameters (the port diameter, plate thickness, the enlargement factor, the compressed plate pack length, the horizontal port distance, and the vertical port distance) and through the Bees algorithm (BA). The present study achieved three solution sets for the design parameters by investigating the sensitivity of the design parameters heeded in the optimization of the GPHE. The design parameters in these three optimal solution sets were opted for in such a way that heat transfer increased by 41. 6%, 34. 55%, and 20. 7%, and pressure drop decreased by 11. 89%, 27%, and 83%, respectively.

Brushless permanent magnet motors play an important role in many applications. Power density and efficiency are two important factors in designing such motors. This paper proposes a novel approach to design a brushless permanent magnet motor based on optimization of a combination of power density and efficiency. First of all, this paper presents the equation related to the design and dimensions of brushless permanent magnet motor. Then, an optimum design based on bee's algorithm (BA) with the purpose of increasing power density is presented. Finally, Simulation results of a 2-D finite element analysis have well validated the efficiency of the applied method.