An improved method of classic geneticalgorithms is proposed which uses Thread-Level Speculation (TLS) technology for the shortcoming that classic geneticalgorithm's search speed is slow. Unlike the classic genet...
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Diversity technology can effectively resist channel multipath fading,and balanced technology can effectively inhibit the inter-symbol interference,so the diversity technology and balanced technology combined can effec...
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Diversity technology can effectively resist channel multipath fading,and balanced technology can effectively inhibit the inter-symbol interference,so the diversity technology and balanced technology combined can effectively improve the quality of ***,this paper uses parallel genetic algorithm to optimize the space diversity orthogonal wavelet adaptive algorithm,taking the space points on each branch equalizer weight vector as the son species of parallel genetic algorithms for selection,crossover,and mutation;between each species to each other and regularly send the best individual fitness;eliminate the worst individual fitness;and take diversity branch output signal and input orthogonal wavelet adaptive device *** computer simulation results show that the fast algorithm convergence speed and small steadystate errors can achieve the global optimal solution.
An approach for optimization of trading strategies ( algorithms) based on indicators of financial markets and evolutionary computation is described. A new version of differential evolution algorithm for the search for...
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An approach for optimization of trading strategies ( algorithms) based on indicators of financial markets and evolutionary computation is described. A new version of differential evolution algorithm for the search for optimal parameters of trading strategies for maximization of trading profit is used. The experimental results show that this approach can improve several times the profitability of the trading strategies.
This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon ...
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This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently. (C) 2009 Elsevier Ltd. All rights reserved.
A sound speed profile plays an important role in shallow water sound *** with in-situ measurements,many inversion methods,such as matched-field inversion,have been put forward to invert the sound speed profile from ac...
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A sound speed profile plays an important role in shallow water sound *** with in-situ measurements,many inversion methods,such as matched-field inversion,have been put forward to invert the sound speed profile from acoustic ***,the time cost of matched-field inversion may be very high in replica field *** studied the feasibility and robustness of an acoustic tomography scheme with matched-field processing in shallow water,and described the sound speed profile by empirical orthogonal *** analyzed the acoustic signals from a vertical line array in ASIAEX2001 in the East China Sea to invert sound speed profiles with estimated empirical orthogonal functions and a parallel genetic algorithm to speed up the *** results show that the inverted sound speed profiles are in good agreement with conductivity-temperature-depth ***,a posteriori probability analysis is carried out to verify the inversion results.
Image annotation can be formulated as a classification problem. Recently, Adaboost learning with feature selection has been used for creating an accurate ensemble classifier. We propose dynamic Adaboost learning with ...
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Image annotation can be formulated as a classification problem. Recently, Adaboost learning with feature selection has been used for creating an accurate ensemble classifier. We propose dynamic Adaboost learning with feature selection based on parallel genetic algorithm for image annotation in MPEG-7 standard. In each iteration of Adaboost learning, geneticalgorithm (GA) is used to dynamically generate and optimize a set of feature subsets on which the weak classifiers are constructed, so that an ensemble member is selected. We investigate two methods of GA feature selection: a binary-coded chromosome GA feature selection method used to perform optimal feature subset selection, and a bi-coded chromosome GA feature selection method used to perform optimal-weighted feature subset selection, i.e. simultaneously perform optimal feature subset selection and corresponding optimal weight subset selection. To improve the computational efficiency of our approach, master-slave GA, a parallel program of GA, is implemented. k-nearest neighbor classifier is used as the base classifier. The experiments are performed over 2000 classified Corel images to validate the performance of the approaches. (C) 2009 Elsevier K.V. All rights reserved.
P>Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors ...
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P>Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool.
New ways to exploit parallelism of large scientific codes are still researched on. In this paper we present parallelization of the differential evolution algorithm. The simulations are implemented in Java programming ...
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ISBN:
(纸本)9783319321493;9783319321486
New ways to exploit parallelism of large scientific codes are still researched on. In this paper we present parallelization of the differential evolution algorithm. The simulations are implemented in Java programming language using PGAS programing paradigm enabled by the PCJ library. The developed solution has been used to test differential evolution on a number of mathematical function as well as to fine-tune the parameters of nematode's C. Elegans connectome model. The results have shown that a good scalability and performance was achieved with relatively simple and easy to develop code.
High performance computing (HPC) clouds consume a lot of energy (kWh);therefore reducing energy consumption is a high priority for any cloud provider. This paper studies the applications of vector bin packing heuristi...
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ISBN:
(纸本)9781450348157
High performance computing (HPC) clouds consume a lot of energy (kWh);therefore reducing energy consumption is a high priority for any cloud provider. This paper studies the applications of vector bin packing heuristic and Neural Network (NN) to allocate virtual machines (VMs) onto physical machines (PMs) that minimizes total energy consumption of the physical machines. In our scenario, a list of virtual machines from request queue needs to assign to system for every interval time (T) and minimize total energy consumption. We proposed Best Fit Decreasing Neural Network (BFD-NN), which contains an evaluation function (f) that finds the most efficient physical machine for each VM from requests in system. We also proposed a process to optimize weight of coefficients in f for every request which users submit to the system based on information of users' requests in the past by using parallel genetic algorithm (PGA) and Neural Network. Our method is a new approach because it not only uses knowledge from requests of users but also considers time dimension of virtual machines. Two job parallel workload models in parallel Workloads Archive are used to evaluate our approach. The simulation results illustrate that BFD-NN could reduce up to 15% total energy consumption compared with state-of-the-art heuristics (such as Best Fit and First Fit Decreasing) in online allocation virtual machines.
The use of high performance computing has been gaining more and more followers in the different branches of Science and Engineering given the potential offered to cleat with complex and big problems. However, the para...
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ISBN:
(纸本)9781509020881
The use of high performance computing has been gaining more and more followers in the different branches of Science and Engineering given the potential offered to cleat with complex and big problems. However, the parallel programming paradigm involves additional aspects to the merely functional, which could provoke different kinds of bottlenecks in the performance of the applications. Such diff culties may represent critical obstacles, especially for the non-expert users. In this work, we consider the limitations of the automatic development of parallel applications, and the obstacles in the performance tuning process, and we propose a built-in environment that integrates these both processes in a transparent manner. We call our proposal as Environment for automatic development and tuning of parallel Applications (EPA). EPA follows a cooperative approach: (i) It provides an interface to guide the user in the depiction of the pair problem-solution by completing a form;(ii) such information is automatically formalized in a specif cation;(iii) the specif ed information is automatically used by EPA to instantiate an instrumented skeleton;(iv) the skeleton of the parallel application is a priori enriched in EPA with tuning instrumentation, for monitoring, analysis and tuning actions;(v) the tunable parallel application is automatically generated by EPA;(vi) the user is able to execute the application with no more effort than having completed a form. Clearly, EPA makes transparent the process of code generation and instrumentation, which represents an important advantage especially for non-expert users. Given that the parallelization of any pair problem-solution is hard to generalize, the environment proposes to tackle different parallel problem solvers. The tuning knowledge injected in the generated applications is based on performance models, which makes the decision-making process concise. The Environment could include as problem solvers as needed. In this article, we
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