توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Staffing Software Maintenance Projects with Multiple Service Levels in SLA
نویسنده(ها): ،
اطلاعات انتشار: شانزدهیمن کنفرانس مهندسی برق ایران، سال
تعداد صفحات: ۶
Today outsourcing a software system's maintenance is common in software industry. Software maintenance organizations need to estimate the size of software maintenance team, in order to make decisions about acceptance or rejection of a project. In this paper we present a method to estimate the optimal staffing needed for a project that has multiple service levels with different priority and response time. The priority and response time determined with a SLA. We use results of queuing theory to model the maintenance environment with non–preemptive priority M\M\c queue. We also show that response time of an arbitrary request can not be less than a specified time<\div>

۲A Multi–Role Cellular PSO for Dynamic Environments
نویسنده(ها): ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۶
In real world, optimization problems are usually dynamic in which local optima of the problem change. Hence, in these optimization problems goal is not only to find global optimum but also to track its changes. In this paper, we propose a variant of cellular PSO, a new hybrid model of particle swarm optimization and cellular automata, which addresses dynamic optimization. In the proposed model, population is split among cells of cellular automata embedded in the
search space. Each cell of cellular automata can contain a specified number of particles in order to keep the diversity of swarm. Moreover, we utilize the exploration capability of quantum particles in order to find position of new local optima quickly. To do so, after a change in environment is detected, some of the particles in the cell change their role from standard particles to quantum for few iterations. Experimental results on moving peaks benchmark show that the
proposed algorithm outperforms mQSO, a well–known multi swarm model for dynamic optimization, in many environments.<\div>

۳Adaptive Parameter Selection Scheme for PSO: A Learning Automata Approach
نویسنده(ها): ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۹
PSO, like many stochastic search methods, is very sensitive to efficient parameter setting. As modifying a single parameter may result in a large effect. In this paper, we propose a new a new learning automatabased approach for adaptive PSO parameter selection. In this approach three learning automata are utilized to determine values of each parameter for updating particles velocity namely inertia weight, cognitive and social components. Experimental results show that the proposed algorithms compared to other schemes such as SPSO, PSO–IW, PSO TVAC, PSO–LP, DAPSO, GPSO, and DCPSO have the same or even higher ability to find better local minima. In addition, proposed algorithms converge to stopping criteria significantly faster than most of the PSO algorithms<\div>

۴Identification of Web Communities using Cellular Learning Automata
نویسنده(ها): ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۱۱
A collection of web pages which are about a common topic and are created by individuals or any kind of associations that have a common interest on that specific topic is called a web community. Since at present, the size of the web is over 3 billion pages and it is still growing very fast, identification of web communities has become an increasingly hard task. In this paper, a method based on asynchronous cellular learning automata (ACLA) for identification of web communities is proposed. In the proposed method first an asynchronous cellular learning automaton is used to determine the related pages and their relevance degree (the relationship structure of web pages). For determination of relationship structure of web pages information about hyperlinks and the users’ behaviour in visiting the web pages are used. Then, an algorithm similar to the HITS algorithm is applied on the obtained structure to identify the web communities. One of the advantages of the proposed method is that the web community obtained using this method is not dependent on a specific web graph structure. To evaluate the proposed approach, it is implemented and the results are compared with the results obtained for two existing methods, HITS and a complete bipartite graph based method. Experimental results show the superiority of the proposed method.<\div>

۵Learning Automata Based Artificial Immune System for Data Classification
نویسنده(ها): ،
اطلاعات انتشار: چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۶
In this paper we propose an artificial immune system in which learning automata are used to adaptively determine the values of its parameters. Learning automata are used for altering the shape of receptor portion of antibodies to better complementarily match the confronted antigen. In order to show the effectiveness of the proposed artificial immune computer experiments have been conducted. The result of experimentations confirms the effectiveness of the proposed model<\div>

۶Bandwidth Allocation in WiMAX networks using Reinforcement Learning
نویسنده(ها): ،
اطلاعات انتشار: سیزدهمین کنفرانس دانشجویی مهندسی برق ایران، سال
تعداد صفحات: ۷
An important problem for the WiMAX networks is how to provide a guaranteed quality of service for applications. A key aspect of this problem is how BSs should share bandwidth capacity between different classes of traffic. This decision needs to be made for each incoming packet, and is known as the packet scheduling problem. A major challenge in packet scheduling is that the behavior of each traffic class may not be known in advance, and can vary dynamically. In this paper, we describe how we have modeled the packet scheduling problem as an application for reinforcement learning (RL). We demonstrate how our RL approach can learn scheduling policies that satisfy the quality of service requirements of multiple traffic classes under a variety of conditions. The proposed solution has been designed to have an ability to accommodate integrated traffic in the networks with effective scheduling schemes. A series of simulation experiments have been carried out to evaluate the performance of the proposed scheduling algorithm. The results reveal that the proposed solution performs effectively to the integrated traffic composed of messages with or without time constraints and achieves proportional fairness among different types of traffic.<\div>

۷a mapping algorithm for highly heterogeneous computational grid: a learning automata approach
نویسنده(ها): ،
اطلاعات انتشار: دهمین کنفرانس سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۸
the computational grid provides a platform for exploiting various computational resources over wide area network.one concern in implementing computational grid environment is how to effectively map tasks onto resources in order to gain high utilization in the highly heterogeneous environment of the grid in this paper a mapping algorithm based on learning automata is proposed the results of experiments show that the proposed algorithm can obtain better performance compared to the two best existing algorithms in high task and machine heterogeneous environments .<\div>

۸a new evolutionary computing model based on cellular learning automata
نویسنده(ها): ،
اطلاعات انتشار: دهمین کنفرانس سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۸
in this paper a new evolutionary computing model called CLA–EC is proposed this new model is a combination of a model called cellularlearning automata CLA and the evolutionary model in this new model each genome is assigned to a cell of cellular learning automata to each of which a se t of learning automata is assigned . the set of actions selected by the set of automata associated to a cell determines the genome'sstringfor that cell based on a local rule a reinforcement signal vector is generated and given to the set learning automata residing in the cell.based on the received signal each learning automaton updates its internal structure according to a learning algorithm<\div>

۹asymptotic behavior learning automata operating in state dependent nonstationary environments
نویسنده(ها): ،
اطلاعات انتشار: دهمین کنفرانس سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۶
in this paper we intorduce a new state dependent nonstationary environment and study the asymptotic behavior of SLrI learning algorithm operating under the proposed environment it is shown that the SLR–I automaton operating in the proposed nontationary environment equalizes the expected penalty strengths of actions this model was motivated by applications of learning automata in call admission in cellular networks<\div>

۱۰asynchronous cellular learning automata
نویسنده(ها): ،
اطلاعات انتشار: دهمین کنفرانس سالانه انجمن کامپیوتر ایران، سال
تعداد صفحات: ۱۰
in this paper we introduce asynchronous cellular learning automata and then study its convergence behavior. It is shown that for class of rules called commutative rules the asynchronous cellular learning automata converges to a stable and compatible configuation the numerical results also confirms the theory<\div>

۱۱A New Discrete Binary Particle Swarm Optimization based on Learning Automata
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس سراسری سیستم های هوشمند، سال
تعداد صفحات: ۱۵
The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social–psychological metaphor. A population of particle adapts by returning stochastically toward previously successful regions in the search space and is influenced by the successes of their topological neighbors. In this paper we propose a learning automata based discrete binary particle swarm algorithm. In the proposedalgorithm the set of learning automata assigned to a particle may be viewed as the brain of the particle determining its position from its own and other particles past experience. The numerical results show that the performance of the proposed algorithm is better than Kennedy’s approach for some of test bed problems<\div>

۱۲an optimal channel assignment scheme
نویسنده(ها): ،
اطلاعات انتشار: یازدهمین کنفرانس مهندسی برق، سال
تعداد صفحات: ۸
In this paper we introduce an optimal channel assignment algorithm for two traffic classes :voice and data which maintains predefined upper bounds on the dropping probabilities of both handoff transaction and handoff voice calls in cellular mobile networks the proposed channel assignment scheme minimizes blocking probability of both types of new calls subject to the hard constraint on dropping probabilities of handoff transaction calls and handoff voice calls the proposed channel assignment scheme can easily be extended to multi –classes traffics.<\div>
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