Under the guidance of scientific and technological innovation concept, new technology and algorithms are applied to information retrieval and real estate registration system. These excellent algorithms and hardware te...
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Under the guidance of scientific and technological innovation concept, new technology and algorithms are applied to information retrieval and real estate registration system. These excellent algorithms and hardware technology make our file management more convenient, intelligent, and efficient. In this paper, researches on the establishment of intelligent file management system and document retrieval were done based on big data environment and with the combination of the project development experience of the Land and Resources Bureau of Nanjing. First of all, this paper focuses on the defects of Java EE framework which is proposed based on the composite Spring-Struts-Hibernate(SSH) frame system and aims to optimize the performance of SSH and promote its efficiency. Secondly, the growing number of archives is reducing the retrieval efficiency of archives management website. In this paper, the ant colony optimization algorithm is employed to classify the data mining and applied to the quick retrieval of big data. At the same time, the complexity of the optimized algorithm and retrieval efficiency are analyzed. The results show that the retrieval time and efficiency are improved in the big data environment.
An evolution model based on the ant colony optimization algorithm for investment behavior in the stock market is *** largest Lyapunov exponents of the stock price time series created from the model are *** simulation ...
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An evolution model based on the ant colony optimization algorithm for investment behavior in the stock market is *** largest Lyapunov exponents of the stock price time series created from the model are *** simulation results show that this model can not only create stock price trends rather similar to the real stock market,but also show the chaotic behavior like the real stock *** observed that the more speculators among the investors the bigger the largest Lyapunov exponent and the stronger the chaotic behavior in stock markets.
Optimizing the cloud platform and resources scheduling is the important thing on cloud *** optimizing the running time and resource costs,we proposed a model(ACO-HS) mixing the ant colony optimization algorithm and ha...
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Optimizing the cloud platform and resources scheduling is the important thing on cloud *** optimizing the running time and resource costs,we proposed a model(ACO-HS) mixing the ant colony optimization algorithm and harmony search ***-HS can effectively retain the high accuracy and parallelism of ACO algorithm,and combine with the capabilities of fast global search from HS *** the simulation experiment on the Cloud Sim software,ACO-HS model has been proved that it will perform well in the scheduling time and the resource utilization.
Fault-tolerant scheduling of real-time (RT) tasks in multiprocessor environment is essentially a NP-hard problem. This basically involves allocating a set of tasks to a set of processors so as to minimize the makespan...
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ISBN:
(纸本)9781479938384
Fault-tolerant scheduling of real-time (RT) tasks in multiprocessor environment is essentially a NP-hard problem. This basically involves allocating a set of tasks to a set of processors so as to minimize the makespan and ensure tasks to meet their timing constraints. Many traditional heuristic approaches, such as earliest deadline first (EDF) and least laxity first (LLF) have been adopted to find optimal solution to this scheduling problem. However, conventional approach to achieve fault-tolerance (FT) in scheduling RT tasks based on traditional heuristic approach suffers from poor performance and results in inefficient processor utilization. Nature-inspired heuristic algorithms are gaining increased acceptance among researcher for solving real world NP-hard combinatorial optimization problems. This paper presents a comparative study of the novel primary-backup (PB) based fault-tolerant scheduling (PBFTS) technique for RT tasks in multiprocessor environment using two popular nature-inspired heuristic algorithms: the antcolonyoptimization (ACO) and the Genetic algorithm (GA). Exhaustive simulation reveals that the PBFTS algorithm based on GA and ACO both outperform the traditional PBFTS schemes in terms of performance, system utilization and efficiency. However, the comparative study also shows that the ACO based scheme surpasses the GA based scheme in terms of speed of execution whereas GA based scheme displays superior convergence with respect to ACO counterpart.
Recently, there has been much more attention focusing on the evolving networks, whose application domains include Web networks, social networks, communication networks and etc. In this paper, we focus on a financial n...
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ISBN:
(纸本)9781479974931
Recently, there has been much more attention focusing on the evolving networks, whose application domains include Web networks, social networks, communication networks and etc. In this paper, we focus on a financial network, where nodes represent participants of a financial market. Due to lending activities, funds are transferred from one participant to another, and credit-debt relationships between them are formed. With repeated activities, flows of funds are shown in a financial network We analyze the evolution of funds flows based on evolutionary game theory. Using Lyapunov stability method, we prove that funds flows converge to a relatively stable state, and prove a bound on the convergence time. Finally, we design an ant colony optimization algorithm for a financial network, and use experiments to simulate the evolving process of funds flows.
This study examines the estimation of parameters for the Shifted Weibull Distribution (SWD) using several robust metaheuristic algorithms, with a focus on enhancing precision and reliability in investment data analysi...
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Fault-tolerant scheduling of real-time (RT) tasks in multiprocessor based systems is essentially a NP-hard problem. Basically this is a permutation based combinatorial optimization problem which involves allocating a ...
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ISBN:
(纸本)9781479980826
Fault-tolerant scheduling of real-time (RT) tasks in multiprocessor based systems is essentially a NP-hard problem. Basically this is a permutation based combinatorial optimization problem which involves allocating a set of tasks on a set of processors so as to minimize the makespan and ensures tasks to meet their timing constraints. Conventional approach to meet fault-tolerance (FT) in scheduling RT tasks based on traditional heuristic approach yields poor performance, like inefficient processor utilization and higher task rejection. The primary-backup (PB) scheme is a popular approach used as a fault-tolerant technique to schedule RT tasks with guarantee to meet their deadlines despite presence of fault. In this paper, we propose a novel scheduling algorithm using discrete elitist multi-objective antcolonyoptimization (DEMACO) technique for providing FT in multiprocessor environment. Exhaustive simulation study reveals that the proposed primary-backup based fault-tolerant scheduling (PBFTS) scheme using DEMACO outperforms other traditional fault-tolerant scheduling schemes in terms of performance, system utilization and efficiency.
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