To date, various paradigms of soft-Computing have been used to solve many modern problems. Among them, a self organizing combination of fuzzy systems and neural networks can make a powerful decision making system. Her...
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Initialization parameters of Self-organizing map networks (SOM) have a great influence in their final result. This is the only known problem of SOM networks. The uncertainty of solution is resolved with the fusion met...
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Initialization parameters of Self-organizing map networks (SOM) have a great influence in their final result. This is the only known problem of SOM networks. The uncertainty of solution is resolved with the fusion methods in many machine learning algorithms. Motivated by this application, we aim to reduce the uncertainty in SOM final result and provide a more robust solution. This is done by aggregating the results obtained from several run of SOM network. The objective in uniting several SOM run is to reduce the effect of two above factors and reach a more appropriate solution. To achieve this, a number of methods for integration of SOM solutions have been proposed and their characteristics are discussed in detail. Finally, these approaches are experimentally compared with some recently proposed SOM networks and their effectiveness are investigated.
In this paper a novel unsupervised classification method for electrocardiogram (ECG) signal classification is presented. The proposed approach classifies the input signal into normal and abnormal heartbeat patterns wi...
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A novel recursive singularity free FTSM (Fast Terminal Sliding Mode) strategy for finite time tracking control of nonholonomic systems is proposed. As a result, the singularity problem around the origin resulting from...
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Modeling the generation of a wind farm and its effect on power system reliability is a challenging task,largely due to the random behavior of the output *** this paper,we propose a new probabilistic model for assessin...
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Modeling the generation of a wind farm and its effect on power system reliability is a challenging task,largely due to the random behavior of the output *** this paper,we propose a new probabilistic model for assessing the reliability of wind farms in a power system at hierarchical level II(HLII),using a Monte Carlo *** proposed model shows the effect of correlation between wind and load on reliability *** can also be used for identifying the priority of various points of the network for installing new wind farms,to promote the reliability of the whole system.A simple grid at hierarchical level I(HLI) and a network in the north-eastern region of Iran are *** results showed that the correlation between wind and load significantly affects the reliability.
In this paper, we present our approach to author ranking subtask;which is a part of author-profiling task in RepLab 2014. In this subtask, systems are expected to detect influential authors and opinion makers on Twitt...
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In this paper, we present our approach to author ranking subtask;which is a part of author-profiling task in RepLab 2014. In this subtask, systems are expected to detect influential authors and opinion makers on Twitter website. The systems' output, for a given domain, must be a ranked list of authors according to their probability of being an influential author or opinion maker. Our system utilizes a Time-sensitive Voting algorithm, which is based on the hypothesis that influential authors tweet actively about topics of their interest. In this method, hot topics of each domain are extracted and a time-sensitive voting algorithm ranks each authors on their respective topics.
An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention ...
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An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention is considered in the multiprocessor scheduling problem. A linear switching-state space-modeling paradigm is introduced to enable theoretical analysis from a system engineering perspective. Theoretical analysis of this model shows its robustness against changes in processing power and link failure. The proposed algorithm uses a fuzzy decision-making procedure to handle changes in the multiprocessor system. The efficiency of the proposed algorithm is illustrated by several random experiments and comparison against a recent benchmark approach. The results show up to 18% average improvement in makespan, especially for larger scale systems.
This paper proposes a new state observer for nonlinear systems with non negligible and different time delays in the state, output and input and Lipschitz nonlinearity. The proposed observer is composed of a chain of o...
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Coronary artery heart disease is one of the main reasons of death in under development countries such as Iran. Based on vagueness in data and uncertainty in decision making finding an optimal way for diagnosis would b...
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In this paper, a fuzzy variance analysis model with interaction between explanatory variables using Tanaka's model is investigated. A linear programming model is formulated for measuring the value of response fact...
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