The present work is concerned with the two-body problem with varying mass in case of isotropic mass loss from both components of the binary systems. The law of mass variation used gives rise to a perturbed Keplerian problem depending on two small parameters. The problem is treated analytically in the Hamiltonian frame-work and the equations of motion are integrated using the Lie series developed and applied, separately by Delva (1984) and Hanslmeier (1984). A second order theory of the two bodies eject mass is constructed, returning the terms of the rate of change of mass up to second order in the small parameters of the problem.
Problem statement:The prediction is very useful in solar energy applications because it permits to estimate solar data for locations where measurements are not available. The developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. Approach: The forecasting ability of some models could be further enhanced with the use of additional meteorological parameters. After having simulated many different structures of neural networks and trained using measurements as training data, the best structures were selected in order to evaluate their performance in relation with the performance of a neuro-fuzzy system. As the alternative system, ANFIS neuro-fuzzy system was considered, because it combines fuzzy logic and neural network techniques that are used in order to gain more efficiency. ANFIS is trained with the same data. Results: The comparison and the evaluation of both of the systems were done according to their predictions, using several error metrics. Fuzzy model was trained using data of daily solar radiation recorded on a horizontal surface in National Research Institute of Astronomy and Geophysics, Helwan, Egypt (NARIG) at ten years (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000). Conclusion: The predicting conclusion indicated that the TS fuzzy model gave a good accuracy of approximately 96% and a root mean square error lower than 6%.
Solar energy can be converted directly into electricity by means of solar cells. Solar cells currently cost around $3.50 per watt for crystalline cells and $2 per watt for thin-film wafers, which are less efficient but can be integrated into building materials. Industry analysts note that between 2000 and 2005, each doubling of cumulative production resulted in a price drop of 20%. Some maintain that prices may fall even more dramatically in the future. Meanwhile the conversion efficiency has been increased more than expected. Furthermore improvements and cost reductions are expected, not only of cells but also of the solar cell modules and solar cell systems. In the development of PV much attention is given to however, the present market which is still dominated by crystalline silicon. The market might grow until multi-thousand MW a year in the next century. PV module can be a return by the same cost after five year installed the high energy consumption rate per m2 and the intensive utilization of Arab World. Assessment studies indicate that on houses and building (roofs, walls) it might be possible to install a PV generating capacity of 50,000 Megawatt, assuming a conversion efficiency of the system of 14.7%. Such a system might be able to produce 50 Terra-watt, hour per year, about 70% of the electricity consumption we are facing today
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