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The idea of opposition-based learning was introduced 10 years ago. Since then a noteworthy group of researchers has used some notions of oppositeness to improve existing optimization and learning algorithms. Among others, evolutionary algorithms, reinforcement agents, and neural networks have been reportedly extended into their “opposition-based” version to become faster and/or more accurate. However,...
This paper proposes a methodology to create an interpretable fuzzy model for monthly rainfall time series prediction. The proposed methodology incorporates the advantages of artificial neural network, fuzzy logic and genetic algorithm. In the first step, the differences between the time series data are calculated and they are used to define the interval between the membership functions of a Mamdani-type...
This article introduces a new strategy to detect a ventricular premature beat (VPB). The strategy utilized a swarm fuzzy inference system (SFIS) and features of the R wave of electrocardiogram. SFIS was a FIS optimized using particle swarm optimization (PSO). The PSO was used to find the optimal parameters of the FIS. The fuzzification part of the FIS used a Gaussian function. The inputs of the FIS...
With increasing adoption of SOA and Cloud Computing technologies where IT including infrastructure, platforms and applications are delivered as services, there is increasing use of a shared resource model where computing and IT resources are shared across multiple applications, so accordingly there is increasing need for solutions that optimize the resource allocation. Power, cooling and real estate...
Accuracy of forecasting in fuzzy based prediction system considerably depends on subjectively decided parameters such as fuzzy membership function. In this paper, we presented a novice concept to optimize Ordered Weight Aggregation (OWA) based forecasting model by Genetic Algorithm. Firstly, OWA weights are determined on the basis of importance of fuzzy set in the system by employing regularly increasing...
Measuring the performance of a given classifier is not a straightforward or easy task. Depending on the application, the overall classification rate may not be sufficient if one, or more, of the classes fail in prediction. This problem is also reflected in the feature selection process, especially when a wrapper method is used. Cohen's kappa coefficient is a statistical measure of inter-rater agreement...
In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications...
A fuzzy approach to real-time calibration of mobile laser rangefinder is presented as an alternative to the methods based on adaptive algorithms. The main error source in such a measurement system is drift error due to the changes of ambient temperature. It may be compensated using repeatedly performed calibration based on the time-of-flight measurement of laser pulse propagating through the constant...
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