Throughout the present manuscript, we are going to introduce a novel group emergency decision-making technique in which the application of prospect theory explains the psychological behaviour of the decision maker who is affected by the hesitancy and uncertainty of cognition in decision making problems.\Instead of usual aggregation procedure, we implement here a new fusion technique that ...

In this paper, we propose a context-sensitive technique for unsupervised change detection in multitemporal remote sensing images. The technique is based on fuzzy clustering approach and takes care of spatial correlation between neighboring pixels of the difference image produced by comparing two images acquired on the same geographical area at different times. Since the ranges of pixel values o...

Glaucoma is an ocular disease that causes permanent blindness if not cured at early stage. Cup-to-disk ratio (CDR), obtained by dividing the height of optic cup (OC) with disk (OD), a widely adopted metric used for glaucoma screening. Therefore, accurately segmenting OD and OC crucial calculating CDR. Most methods have employed deep learning segmentation OC. However, these are very time consumi...

in this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. this technique uses synchronized phasors measured by phasor measurement units (pmus) in a wide-area measurement system. in order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy ...

Intrusion Detection Systems (IDS) form a key part of system defence, where it identifies abnormal activities happening in a computer system. In recent years different soft computing based techniques have been proposed for the development of IDS. On the other hand, intrusion detection is not yet a perfect technology. This has provided an opportunity for data mining to make quite a lot of importa...

Adaptive Fuzzy Logic Systems trained by genetic evolution of their parameters are presented in this work. This technique is based on the aggregation of parameter perturbations. Neither the evaluation function nor the membership functions, have to be differentiable as required in most optimization techniques. In the classical Genetic Algorithms, the solution space of each parameter should be spe...

This paper addresses the problem of tuning the input and the output parameters of a fuzzy logic controller. The system learns autonomously without supervision or a priori training data. Two novel techniques are proposed. The first technique combines Q(λ)-learning with function approximation (fuzzy inference system) to tune the parameters of a fuzzy logic controller operating in continuous state...

Regression testing is an immensely important process in the maintenance phase. The prioritization of test case becomes all the more important owing to the fact that it is not feasible to run all the test cases after each and every change. The proposed work dwells on the power of fuzzy expert system to make decisions which are better than the normal expert systems. The technique uses concepts li...