A Comparative Study of Three Artificial Intelligence Techniques: Genetic Algorithm, Neural Network, and Fuzzy Logic, on Scheduling Problem

2014 ◽  
Author(s):  
Abdollah Ansari ◽  
Azuraliza Abu Bakar
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Comparative Study ◽  
Scheduling Problem ◽  
Artificial Intelligence Techniques

scholarly journals Survey on computational intelligence based image encryption techniques

2020 ◽  
Vol 19 (3) ◽  
pp. 1428
Author(s):  
Thirumalaimuthu Ramanathan ◽  
Md. Jakir Hossen ◽  
Md. Shohel Sayeed ◽  
Joseph Emerson Raja
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Genetic Algorithm ◽  
Image Encryption ◽  
Computational Intelligence ◽  
Visual Cryptography ◽  
Machine Learning Algorithms ◽  
Artificial Intelligence Techniques ◽  
Cryptographic Keys

Image encryption is an important area in visual cryptography that helps in protecting images when shared through internet. There is lot of cryptography algorithms applied for many years in encrypting images. In the recent years, artificial intelligence techniques are combined with cryptography algorithms to support image encryption. Some of the benefits that artificial intelligence techniques can provide are prediction of possible attacks on cryptosystem using machine learning algorithms, generation of cryptographic keys using optimization algorithms, etc. Computational intelligence algorithms are popular in enhancing security for image encryption. The main computational intelligence algorithms used in image encryption are neural network, fuzzy logic and genetic algorithm. In this paper, a review is done on computational intelligence-based image encryption methods that have been proposed in the recent years and the comparison is made on those methods based on their performance on image encryption.

The Application of Artificial Intelligence in Power System State Estimation with Intelligent Materials

2012 ◽  
Vol 485 ◽  
pp. 131-135 ◽  
Author(s):  
Yun Jing Liu ◽  
Feng Wen Wang
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Power Systems ◽  
Power System ◽  
State Estimation ◽  
Real Time ◽  
System State ◽  
Power System State Estimation ◽  
Artificial Intelligence Techniques

With the development of power systems, the problem of security, stability and economics has become increasingly important. Reliable real-time data base is the foundation of analysis of the systems security and stability. Power system state estimation is used to build reliable real-time model of the power network. It has the on-line security analysis function. Power systems are large, complex systems containing highly nonlinear components. Therefore, traditional approaches often have difficulties in finding the optimal solution efficiently. Artificial intelligence techniques are being applied to a wide range of practical problems in power system. With their ability to some laws of nature and mimic human reasoning, AI techniques such as fuzzy logic and genetic algorithm seem to be more efficient in dealing with large systems and complex problems. Artificial intelligence techniques have been applied in power system applications. This paper presents a method of adaptive genetic algorithm and fuzzy logic applied in phasor measurement placement and bad data identification. And simulation is evaluated on IEEE 22-bus power system.

scholarly journals Artificial Intelligence Techniques for Phishing Detection

2019 ◽  
Vol 8 (11) ◽  
pp. 2330-2335
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Neural Systems ◽  
Element Determination ◽  
Artificial Intelligence Techniques ◽  
The Neural Network ◽  
Proper Number ◽  
Phishing Detection

The objective of this undertaking is to apply neural systems to phishing email recognition and assess the adequacy of this methodology. We structure the list of capabilities, process the phishing dataset, and execute the Neural Network frameworks. we analyze its exhibition against that of other real Artificial Intelligence Techniques – DT , K-nearest , NB and SVM machine.. The equivalent dataset and list of capabilities are utilized in the correlation. From the factual examination, we infer that Neural Networks with a proper number of concealed units can accomplish acceptable precision notwithstanding when the preparation models are rare. Additionally, our element determination is compelling in catching the qualities of phishing messages, as most AI calculations can yield sensible outcomes with it.

Image Recognition Technology Based on Artificial Intelligence

2013 ◽  
Vol 347-350 ◽  
pp. 3537-3540
Author(s):  
Hai Yun Lin ◽  
Yu Jiao Wang ◽  
Jian Chun Cai
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Feature Extraction ◽  
Image Retrieval ◽  
Semantic Feature ◽  
Current Image ◽  
Semantic Feature Extraction

In respect of the classification of current image retrieval technology and the existing issues, the paper put forward a method designed for image semantic feature extraction based on artificial intelligence. The new method has solved the tough problem of image semantic feature extraction, by fusing fuzzy logic, genetic algorithm and artificial neural network altogether, which greatly improved the efficiency and accuracy of image retrieval.

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