In general, relative permeability data can be obtained from laboratory coreflooding experiments. Such experimental data can be interpreted analytically or numerically. Compared to analytical methods, when the numerica...
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In general, relative permeability data can be obtained from laboratory coreflooding experiments. Such experimental data can be interpreted analytically or numerically. Compared to analytical methods, when the numerical inversion methods are applied to interpret the coreflooding experimental data, the reservoir performance obtained prior to and after breakthrough can be utilized comprehensively, the capillary effects and the heterogeneity of core samples can also be taken into account, so the estimated result is not only accurate but also complete. Moreover, the numerical inversion methods can be applied to large-scale reservoirs. This article introduces systematically the methodology of numerical inversion methods, and then reviews the present research status. Finally, several proposals of implicitly estimating relative permeability data are put forward from aspects of optimization algorithms’ properties, estimation of endpoint saturations and treatment scale by automatic history matching.
In trading in currency markets, reducing te mean of absolute or squared errors of predicted values is not valuable unless it results in profits. A trading rule is a set of conditions that describe when to buy or sell ...
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In trading in currency markets, reducing te mean of absolute or squared errors of predicted values is not valuable unless it results in profits. A trading rule is a set of conditions that describe when to buy or sell a currency or to close a position, which can be used for automated trading. To optimize the rule to obtain a profit in the future, a probabilistic method such as a genetic algorithm (GA) or genetic programming (GP) is utilized, since the profit is a discrete and multimodal function with many parameters. Although the rules optimized by GA/GP reportedly obtain a profit in out-of-sample testing periods, it is hard to believe that they yield a profit in distant out-of-sample periods. In this paper, we first consider a framework where we optimize the parameters of the trading rule in an in-sample training period, and then execute trades according to the rule in its succeeding out-of-sample period. We experimentally show that the framework very often results in a profit. We then consider a framework in which we conduct optimization as above and then execute trades in distant out-of-sample periods. We empirically show that the results depend on the similarity of the trends in the training and testing periods.
Application of Genetic algorithm and artificial immunization algorithm on getting atmosphere refractivity profile form radar sea clutter (RFC) is introduced. GA can satisfy the nonlinearity, complexity and other speci...
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Application of Genetic algorithm and artificial immunization algorithm on getting atmosphere refractivity profile form radar sea clutter (RFC) is introduced. GA can satisfy the nonlinearity, complexity and other special requirements of RFC. Artificial Immune algorithm can avoid the problems of getting into local optimization, population variety decreasing, and other problems caused by using GA, and the convergence can be improved. The two algorithms are analyzed using the data of radar sea clutter, air sounding, and so on which are acquired in the south sea field, and the quality of two algorithms is gotten, which can be the reference of solving the problem of RFC.
Network planning technology could be used to represent project plan management, such Critical Path Method (CPM for short) and Performance Evaluation Review Technique (PERT for short) etc. Aiming at problem that how to...
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Network planning technology could be used to represent project plan management, such Critical Path Method (CPM for short) and Performance Evaluation Review Technique (PERT for short) etc. Aiming at problem that how to find hypo-critical path in network planning, firstly, properties of total float. free float and safety float are analyzed, and total float theorem is deduced on the basis of above analysis; and secondly, simple algorithm of finding the hypo-critical path is designed by using these properties of float and total theorem, and correctness of the algorithm is analyzed. Proof shows that the algorithm could realize effect of whole optimization could be realized by part optimization. Finally, one illustration is given to expatiate the algorithm.
This paper presents a simple, efficient, real number encoding genetic algorithm. The algorithm has omitted the workload of encoding and selection, it adopts deterministic induced crossover and mutation operators to im...
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ISBN:
(纸本)9780769547923
This paper presents a simple, efficient, real number encoding genetic algorithm. The algorithm has omitted the workload of encoding and selection, it adopts deterministic induced crossover and mutation operators to improve the algorithm's ability of local convergence;And introduced foreign populations by the theory of the bee evolution genetic algorithm, which has strengthened the capacity of mining the information contained in the population optimal individual. This algorithm is not need to improve the overall fitness of the population, but using genetic algorithm processes to achieve the optimal search. We have verified the algorithm through JAVA and MATLAB, the results show that this algorithm can obtain the optimal solution within certain accuracy in 10 generations.
In this study, we developed the Allometric Scaling and Resource Limitations (ASRL) model by using the best GLAS tree heights to optimize the ASRL. At first, we obtained the best metric of GLAS tree heights by comparin...
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ISBN:
(纸本)9781467311601
In this study, we developed the Allometric Scaling and Resource Limitations (ASRL) model by using the best GLAS tree heights to optimize the ASRL. At first, we obtained the best metric of GLAS tree heights by comparing with LVIS tree heights in six sites. Then, the best metric GLAS tree heights were separately used to optimize ASRL model and test the accuracy of prediction heights from optimized ASRL model in sites scale and country scale. Validation result showed that predicted tree heights from optimized ASRL model had high accuracy.
A new method of optimization recently made popular in the evolutionary computation (EC) community is introduced and applied to several electromagnetics design problems. First, a functional overview of the covariance m...
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A new method of optimization recently made popular in the evolutionary computation (EC) community is introduced and applied to several electromagnetics design problems. First, a functional overview of the covariance matrix adaptation evolutionary strategy (CMA-ES) is provided. Then, CMA-ES is critiqued alongside a conventional particle swarm optimization (PSO) algorithm via the design of a wideband stacked-patch antenna. Finally, the two algorithms are employed for the design of small to moderate size aperiodic ultrawideband antenna array layouts (up to 100 elements). The results of the two electromagnetics design problems illustrate the ability of CMA-ES to provide a robust, fast and user-friendly alternative to more conventional optimization strategies such as PSO. Moreover, the ultrawideband array designs that were created using CMA-ES are seen to exhibit performances surpassing the best examples that have been reported in recent literature.
The dissertation puts forward a network model based on analysis of energy constrained multicast routing optimization algorithm. Combined network model, energy model, combination of extreme elements and improved geneti...
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The dissertation puts forward a network model based on analysis of energy constrained multicast routing optimization algorithm. Combined network model, energy model, combination of extreme elements and improved genetic algorithms, it presents an energy constrained QoS multicast routing optimization algorithm. The simulation result shows that the algorithm is feasible and effective and provides an available approach to Ad Hoc networks QoS multicast routing.
According to the controllability of pulse times and the amount of jumps in the states at these times in the process of fed-batch culture producing 1,3-propanediol, this paper proposes a terminal optimal control model,...
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According to the controllability of pulse times and the amount of jumps in the states at these times in the process of fed-batch culture producing 1,3-propanediol, this paper proposes a terminal optimal control model, whose constraint condition is the nonlinear impulsive delay system. The existence of optimal control is discussed and an optimization algorithm which is applied to each subinternal over one cycle for this optimal control problem is constructed. Finally, the numerical simulations show that the terminal intensity of producing 1,3-propanediol has been increased obviously.
Tate pairings has found several new applications in cryptography. However, how to compute Tate pairing is a research focus in all kinds of applications of pairing-based cryptosystems (PBC). In the paper, the structure...
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Tate pairings has found several new applications in cryptography. However, how to compute Tate pairing is a research focus in all kinds of applications of pairing-based cryptosystems (PBC). In the paper, the structure of Miller's algorithm is firstly analyzed, which is used to implement Tate pairing. Based on the characteristics that Miller's algorithm will be improved tremendous if the order of the subgroup of elliptic curve group is low hamming prime, a method of generating primes with low hamming is presented. Then, a new method for generating parameters for PBC is put forward, which enable it feasible that there is certain some subgroup of low hamming prime order in the elliptic curve group generated. Moreover, an optimization implementation of Miller's algorithm for computing Tate pairing is given. Finally, the computation efficiency of Tate pairing using the new parameters for PBC is analyzed, which saves 25.4% of the time to compute the Tate pairing.
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