Optimizing the Garch Model–An Application of Two Global and Two Local Search Methods

Results from our optimization exercise clearly show the advantage of using the random search algorithms when we anticipate the search for the global optimum to be difficult. When the number of parameters in the model is relatively small (nine parameters) Differential Evolution performs better than Genetic Algorithm. However, when the number of parameters in the model is relatively large (fifteen parameters) the reverse case is true. A comparison of the Quasi-Newton and Simplex methods also shows that both the Quasi-Newton algorithm of shazam and the simplex algorithm of fminsearch are sensitive to starting values. However, allowing shazam to set its starting values or using the PRESAMP option to set the starting values produced the best results for shazam. The general conclusion of this paper is that the choice of optimization technique for difficult optimization problems like the one attempted here should be based on problem attributes. When in doubt, multiple techniques should be applied and the estimated results evaluated.     

Promoting photovoltaic electricity usage in developing countries — Experience from Ghana

The awareness of PV systems as a means to provide electricity for remote small towns and villages with small electrical loads has long been recognised. That PV electricity is not widely patronised by the potential end-users can be attributed to lack of awareness of the existence of the technology and the high initial cost of systems which necessarily has to be paid up front. It is argued that demonstration PV systems can be used to awaken awareness. This will open up the dormant large PV market waiting to be tapped in the developing countries, and this will be the benefit of the PV manufacturers who can take advantage of the economies of scale to reduce PV systems production cost and, therefore, a reduced selling price. Suggestions are also made for financing the purchase of PV systems by end-users in the developing countries.     

Mathematical modeling of thin-layer drying kinetics and moisture diffusivity study of apple slices using infrared conveyor-belt dryer

The drying features of apples at different infrared drying settings were investigated. The drying time, moisture-effective diffusion, and activation energy of infrared dried apples were measured experimentally and statistically as a function of slice thicknesses, radiation intensity, and air velocity. The infrared intensity of 0.225, 0.130, and 0.341 W/cm², slice thicknesses of 6, 4, and 2 mm, and airflow of 0.5, 1.0, and 1.5 m/s were used to dry apple slices. The data shows that the drying time reduced as IR increased, but airflow and slice thickness increased. Eight statistical factors were used to compare 11 alternative mathematical drying models. The experimentally acquired drying curves were matched to the thin-layer drying equations. According to the calculations, the Midilli et al. equation had the greatest (efficiency and R²) and lowest (χ², sum of squared errors, standard error of estimate, standard error, standard deviation of difference) values. As a result, this equation is the best for modeling the drying curves of apple slices across all drying circumstances. The optimum moisture diffusivity value varied from 2.59 to 9.07 × 10⁻¹⁰ m²/s. The mean activation energy was determined to be 19.02–29.83 kJ/mol under various experimental conditions.