How to match various components of the Hybrid Electric Vehicle (HEV) and manage the energy distribution is critical for HEV design and control considering that there are at least two sets of energy output systems, the...
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Multiparent crossovers have been validated their outperformance on several optimization problems. However, there are two issues to be considered - the number of parents and the disruptiveness caused by multiple parent...
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This paper presents a methodology to detect on line the physiological state of strains in bioreactor The biologic reactions means that one of the pathways of the metabolism is activated and in this case the microorgan...
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ISBN:
(纸本)0769520189
This paper presents a methodology to detect on line the physiological state of strains in bioreactor The biologic reactions means that one of the pathways of the metabolism is activated and in this case the microorganisms will produce or will consummate The discrete-event system (DES) is synthesised applying the Maximum of Modulus of the Wavelet Transform on measured signals constrained to the biotechnologist expert validation. The determination of Holder Coefficient by Differential Evolutionary algorithms allows to make the difference between different discontinuities and to obtain the segmentation of the signals. All these evaluations leads to associate the signals variations during the time to physiological states.
This paper presents a computational and visualization tool kit for the numerical modeling of 3-D Marangoni and/or magnetically-driven turbulent flows in droplets under normal and/or microgravity conditions. The comput...
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This paper presents a computational and visualization tool kit for the numerical modeling of 3-D Marangoni and/or magnetically-driven turbulent flows in droplets under normal and/or microgravity conditions. The computational part involves the finite element solution of steady-state and transient 3-D Marangoni flows in electrically levitated droplets and the higher order finite difference method for the direction numerical simulation of turbulences in electromagnetically levitated droplets. Both the electrically and magnetically droplets have been used for study of fundamentals governing solidification processing in normal and mciro gravity. The visualization part is developed based on the UNIX/X-motif platform and on the advanced algorithms for mutli-dimensional computer graphics. The visualization tool kit employs the algorithms for data retrieving, partitioning, sorting and searching algorithms, and 3-D/2-D object clipping. An efficient algorithm used for plane and body cutting and particle tracing is presented. The mathematical formulation used in developing the above computational tool kit, including computational and differential geometry, is also discussed. Examples are given to illustrate the effectiveness and efficiency of the tool kit as applied to the numerical simulation and computer visualization of complex steady state and transient three-dimensional Marangoni and turbulent magnetically driven flows in free droplets.
In the field of global optimization, there are many algorithms such as Simulated Annealing Algorithm (SA), Genetic Algorithm (GA), Artificial Neural Network (ANN), and so on. They are all based on the imitation of nat...
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In the field of global optimization, there are many algorithms such as Simulated Annealing Algorithm (SA), Genetic Algorithm (GA), Artificial Neural Network (ANN), and so on. They are all based on the imitation of nature. This paper presents a new global optimization algorithm - statistic inductive algorithm (SIA), which is based on probability theory. The calculated results on some standard testing functions and a 'travelling salesman problem' (TSP) show that SIA is of more effective quality on global optimization than SA and GA. In addition to these results, according to this fundamental optimization idea, this paper analyzed why SA and GA can have effect on global search, and what inherent defects SA and GA have. Reloading optimization code used SIA has been completed. Calculations were performed on various reactor cores. Compared with SA, GA, and Ant System, SIA need less computation time, while the result is much better than them. Conclusion is drawn that SIA is more suitable for in-core fuel management.
Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system th...
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Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process is very helpful. In this paper, we try to create such a system with a genetic algorithm engine to emulate trader behaviour on the foreign exchange market and to find the most profitable trading strategy.
Multiparent crossovers have been validated their outperformance on several optimization problems. However, there are two issues to be considered - the number of parents and the disruptiveness caused by multiple parent...
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Multiparent crossovers have been validated their outperformance on several optimization problems. However, there are two issues to be considered - the number of parents and the disruptiveness caused by multiple parents. We present a tabu multiparent genetic algorithm (TMPGA) to address these two issues by integrating tabu search into the mating of multiparent genetic algorithms. TMPGA utilizes the tabu restriction and the aspiration criterion to sift selected parents in consideration of population diversity and selection pressure. Furthermore, the resulting mating validity further adjusts the number of parents participating in a mating. Experiments are conducted with four common test functions. The results indicate that TMPGA can achieve better performance than both two-parent GA and multiparent GA with the diagonal crossover.
Commercial sensors have generally, due to their own characteristics, some undesirable influences on the measured quantity and its precision. In particular, the dynamic characteristics can be reflected on to the measur...
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Commercial sensors have generally, due to their own characteristics, some undesirable influences on the measured quantity and its precision. In particular, the dynamic characteristics can be reflected on to the measured quantity and lead to false or delayed interpretation of the underlying physical process. The quality and therefore the cost of the sensor is often tied with the dynamic performance of these instruments. Intelligent sensors are able to adapt to changing environments, calibrate themselves, and predict the pattern of the future signal. This paper presents algorithms to improve the dynamic performance of sensors, identify the dynamic characteristics of the sensor, and to predict the future pattern of the measured quantity. In particular, two inverse filters are proposed for the improvement of the sensors dynamic performance. One filter incorporates an optimal constant feedback gain that reduces the computational cost and increases the accuracy. A system identification method is used to identify the sensor's dynamic properties and allows for adaptation of the inverse filter's parameters. This identification algorithm computes the optimum input to the system i.e. the sensor. The optimization is based on the inverse correlation matrix of the information matrix. A genetic algorithm is used to perform both optimizations, for the computation of the optimal input, and for the optimal constant feedback gain. In addition, a predictive filter formulation is given that is based on the identified system. Simulation results indicate that both inverse filters are capable of recovering the original or true signal. The second filter shows superiority in terms of convergence, lower computational cost, and lower error due to its optimized parameters. The predictive filter indicates good working accuracy for the signal prediction.
A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a f...
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Although multi-objective evolutionary algorithm techniques are becoming mature, benchmark measures for evaluating the algorithms still require further research, as convergence theories can hardly be applied here and t...
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