Artificial intelligence applications to security control in power systems

Negnevitsky, M

doi:10.1109/ptc.1999.826456

Cited by 53 publications

(61 citation statements)

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“…In the early 1970s, John Holland, one of the founders' evolutionary computations, introduced the concept of genetic algorithm [8]. Genetic algorithm (GA) is a heuristic method used to find approximate solutions to solve problems through application of the principles of evolutionary biology.…”

Section: Face Emotion Recognition Using Genetic Algorithmmentioning

confidence: 99%

A Comparison of South East Asian Face Emotion Classification Based on Optimized Ellipse Data Using Clustering Technique

Muthukaruppan¹,

Thirugnanam²,

Nagarajan³

et al. 2015

JOIG

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges.In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and has seen improvement compared to the earlier work. 

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Section: Face Emotion Recognition Using Genetic Algorithmmentioning

confidence: 99%

A Comparison of South East Asian Face Emotion Classification Based on Optimized Ellipse Data Using Clustering Technique

Muthukaruppan¹,

Thirugnanam²,

Nagarajan³

et al. 2015

JOIG

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“…This procedure is used to compute the mapping from the input values to the output values, and it consists of three sub-processes, fuzzification, aggregation and defuzzification (Negnevitsky, 2005) as shown in the following figure.…”

Section: Performing Fuzzy Inference Into the Systemmentioning

confidence: 99%

Evaluation of Solar Electric Power Technologies in Jordan Using Fuzzy Logic

Badran

Abdulhadi

Mamlook

2008

ASME 2008 2nd International Conference on Energy Sustainability, Volume 2

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Jordan is considered one of the sun-belt countries, which possesses high solar radiation on its horizontal surface. The present study will be concerned on the uses of fuzzy sets methodology to perform evaluation between the most suitable solar technologies for power generation in Jordan, namely, solar ponds and photovoltaic (PV) technologies. The criterion of the evaluation were based on different parameters, i.e., power capacity, efficiency, availability, capacity factor, storage capability, cost, maturity, land usage and safety, they are planned as the technologies for the near foreseen term. Based on benefit to cost ratios, the results showed that photovoltaic technology found to be the better choice in terms of generating electricity, research and development and more effective programs of support and installation.

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“…3 An artificial neural network a part of artificial intelligence, with its ability to approximate any nonlinear transformation is a good tool for approximation and classification problems. [4][5][6] Multilayer perceptron (MLP), a feed-forward, backpropagation network, is the most frequently used ANN technique in glaucoma research. 7 Artificial Neural Networks (ANNs) have discrete advantages over statistical classification methods.…”

Section: Introductionmentioning

confidence: 99%

Intelligent System using Neural Network Classifier for Glaucoma Diagnosis

Ranadive¹

2018

IJRASET

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Glaucoma is one of the principal causes of blindness in the world 1. It is a condition of eye disease which leads to irreversible blindness in advanced stages. Early diagnosis is an important objective in Glaucoma diagnosis to maintain the best visual acuity throughout the life of the people with Glaucoma. A Neural Network approach is proposed for the diagnosis of Glaucoma. Automated analysis of information from various diagnostic techniques was performed to improve Glaucoma detection in the clinic. This paper discusses the inclusion of neural networks in Glaucoma diagnosis. Data from clinical examination, pachymetry, perimetry and analysis of the retinal nerve fiber layer were integrated in a system of Artificial Intelligence. Analysis of 106 eyes obtained from practicing ophthalmologist, which represent various stages of glaucoma is used to develop an ANN. In Multilayer perceptron, the learning was carried out with 66% of the data and with the training function of gradient descent with momentum backpropagation. The classifier accuracy was. This method provides an efficient and accurate tool for the diagnosis of Glaucoma in the stages of glaucomatous illness by means of ANN.

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Artificial intelligence applications to security control in power systems

Cited by 53 publications

References 0 publications

A Comparison of South East Asian Face Emotion Classification Based on Optimized Ellipse Data Using Clustering Technique

A Comparison of South East Asian Face Emotion Classification Based on Optimized Ellipse Data Using Clustering Technique

Evaluation of Solar Electric Power Technologies in Jordan Using Fuzzy Logic

Intelligent System using Neural Network Classifier for Glaucoma Diagnosis

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