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Improved Memetic Algorithm Enabled Intelligent Multi Agent (IMAEIMA) System for Web Mining

2019 International Journal of Engineering and Advanced Technology  
The proposed work emphasizes an Improved Memetic Algorithm Enabled Intelligent Multi Agent (IMAEIMA) for searching the most appropriate pages when submitting complex queries.  ...  In this proposed system Improved Memetic algorithm additionally enhanced with logarithmic weight function for more accuracy.  ...  A greater enhancement is obtained in the search process using an Intelligent Multi Agent with Improved Memetic Algorithm (IMAEIMA). Fig.1 A.  ... 
doi:10.35940/ijeat.f8811.088619 fatcat:noi72cswrzcnldtuqhygu6yofm

Guest editorial: uncertainty modelling and intelligent information processing

Kok Wai Wong, László T. Kóczy
2010 Memetic Computing  
A total of five papers were selected for publication in this issue.  ...  The objective of this thematic issue is to report on the latest work on new techniques and applications relating to uncertainty modeling and intelligent information processing.  ...  The final paper in this issue is by Attea, titled "A Fuzzy Multi-objective Particle Swarm Optimization for Effective Data Clustering".  ... 
doi:10.1007/s12293-010-0052-5 fatcat:bmo4wazl35edxfcm3gvioa6d2a

Intelligent cloud computing

Mario Pavone, Rabie A. Ramadan, Athanasios V. Vasilakos
2016 Memetic Computing  
It is considered as an excellent platform for AI; however, currently, the integra-B Rabie A. Ramadan rabie@rabieramadan.org  ...  intelligent to intelligent systems.  ...  Instead of using multi-objective heuristic algorithm, e.g. multi-objective genetic algorithms, the manuscript proposes cloud based many objective type-2 fuzzy logic systems on a cloud environment to solve  ... 
doi:10.1007/s12293-016-0214-1 fatcat:4uzilrx3tfge5p63nln4udj2ja

Intelligent feature extraction for ensemble of classifiers

P.V.W. Radtke, R. Sabourin, Tong Wong
2005 Eighth International Conference on Document Analysis and Recognition (ICDAR'05)  
This paper presents a two-level approach to create ensemble of classifiers based on intelligent feature extraction and multi-objective genetic optimization.  ...  To assess the approach's feasibility, a set of tests with isolated handwritten digits is performed.  ...  Multi-Objective Memetic Algorithm Traditional Multi-Objective Genetic Algorithms (MOGA) are based on the Pareto dominance concept.  ... 
doi:10.1109/icdar.2005.146 dblp:conf/icdar/RadtkeSW05 fatcat:ytaz64267zbihd27triwga2icq

A Multi -Perspective Evaluation of MA and GA for Collaborative Filtering Recommender System

Hema Banati, Shikha Mehta
2010 International Journal of Computer Science & Information Technology (IJCSIT)  
This paper presents multi-perspective comparative evaluation of memetic and genetic evolutionary algorithms for model based collaborative filtering recommender system.  ...  Evolutionary approaches like Genetic and memetic algorithms have been considered as one of the most successful approaches for combinatorial optimization.  ...  This paper presents multi-perspective comparative evaluation of memetic algorithm with genetic algorithm for collaborative filtering recommender systems.  ... 
doi:10.5121/ijcsit.2010.2508 fatcat:b4dhrivisndbnporde3ouirb7q

Developing an Effective e-Learning Platform

Noora Yousef A Alomran, Amani Osama M Alameer, Maryam Sami K Alherz, Mohammed Fahed Tayfour, Muneerah Alshabanah, Daniah Alrajhi, Mutasem K. Alsmadi
2020 International Journal of Scientific Research in Science and Technology  
This research aims to design and develop a web-based e-learning system to make the environment of e-learning more adaptive and intelligent for the learners.  ...  Modern institutions, corporations, schools and universities in developed countries believe that e-Learning is a way for educating larger number of students in less time and lesser amount of resources.  ...  A hybrid memetic algorithm with back- propagation classifier for fish classification based on robust features extraction from PLGF and shape measurements.  ... 
doi:10.32628/ijsrst207336 fatcat:a437os5urvcjpaqntfjea6cfea

A Multi-Facet Survey on Memetic Computation

Xianshun Chen, Yew-Soon Ong, Meng-Hiot Lim, Kay Chen Tan
2011 IEEE Transactions on Evolutionary Computation  
In this paper, a comprehensive multi-facet survey of recent research in memetic computation is presented.  ...  Memetic computation is a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving.  ...  To give a multi-facet survey of memetic computation, a review on the more recent memetic algorithms, hybrids and adaptive hybrids is provided.  ... 
doi:10.1109/tevc.2011.2132725 fatcat:dy4vpyft6rhdxb4dkt7iyaqvna

A Survey on Feature Selection Algorithms

Amit Kumar
2015 International Journal on Recent and Innovation Trends in Computing and Communication  
One major component of machine learning is feature analysis which comprises of mainly two processes: feature selection and fe ature extraction.  ...  Due to its applications in several areas including data mining, soft computing and big data analysis, feature selection has got a reasonable importance.  ...  Memetic feature selection algorithm for multi-label classification is developed to prevent premature convergence and gives better accuracy [40] .  ... 
doi:10.17762/ijritcc2321-8169.150431 fatcat:tme4tyl4ijaunbzraka3tey654

Soft computing in remote sensing image processing

Yanfei Zhong, Zexuan Zhu, Yew Soon Ong
2016 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
The fifth paper entitled "Band Selection for Hyperspectral Images Using Probabilistic Memetic Algorithm" presented an adaptive memetic algorithm for hyperspectral image band selection.  ...  methods including PPI, VCA, N-FINDER for DPSO-based endmember extraction algorithm.  ... 
doi:10.1007/s00500-016-2368-7 fatcat:x2bofaqnwfd7fmx7vunh6b7lue

METAHEURISTICHYBRIDIZATION: MEMETICALGORITHM

Stefan Andreea-Mirabela
2020 Annals of the University of Craiova: Economic Sciences Series  
Torefinethepredictionprocess, researchershavedevelopedhybridmodels for forecasting. A famousclass of allthesetechniquesis in themetaheuristicsdomain.  ...  More over, anothergoalistorevealsomepossibilities of metaheuristics, such as hybridization of algorithms.  ...  So, memetic algorithms are computerized intelligence structures that mix various operators to find a solution to optimization problems.  ... 
doaj:1da1c0b6baae445d850036204b262ba4 fatcat:ezkjfryay5g7bdge46tb6m2qyy

A New Deep Learning Approach for Anomaly Base IDS using Memetic Classifier

Shahriar Mohammadi, Amin Namadchian
2017 International Journal of Computers Communications & Control  
The model is based on deep learning approach to learn best features of network connections and Memetic algorithm as final classifier for detection of abnormal traffic.One of the problems in intrusion detection  ...  The model is offered in this paper which tries to use deep learning for detecting best features.An evaluation algorithm is used for produce final classifier that work well in multi density environments.We  ...  For text feature we assign a number for every value of text can give features. For example for service feature we use 0 for Ftp and 1 for Http and so on. After that all feature has a number value.  ... 
doi:10.15837/ijccc.2017.5.2972 fatcat:plisrt3mazee7df6bzfysdk36y

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm.  ...  Two feature functions are used to measure the similarity between chromosomes. The approach considers multiple parallel evolving grids.  ...  and Multi-objective Genetic Algorithm 161, Mary Tom, Computational Intelligence Using Fuzzy Multicriteria Decision Making for DIligenSDietary Intelligence System 172, Gwo-Ruey Yu, Constraints on Control  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

A Detailed Study on Information Retrieval using Genetic Algorithm

Md. Abu Kausar, Md. Nasar, Sanjeev Kumar Singh
2013 Journal of Industrial and Intelligent Information  
In this paper, the applicability of Genetic algorithm (GA) in the field of information retrieval and a review on how a Genetic Algorithm is applied to different problem domains in information retrieval  ...  Genetic Algorithms (GA) are robust and efficient search and optimization techniques inspired by the Darwin's theory of natural evolution.  ...  Thus, for a data retrieval system, a single wrong object among a thousand retrieved objects means total failure.  ... 
doi:10.12720/jiii.1.3.122-127 fatcat:lrzqzstlcvhuhfjs6szqh2fgra

Developing a Smart Nursery Application for Monitoring and Babies Care

Manar Faleh Alqahtani, Reem Saeed Bashunaym, Norah Mohammed Alotaibi, Razan Zeyad Alkhaldi, Muneerah Alshabanah, Daniah Alrajhi, Mutasem K. Alsmadi, Ibrahim Almarashdeh
2020 International Journal of Scientific Research in Science and Technology  
This paper presented a Smart Nursery application for busy parents so that they can ensure the safety and proper care for their babies.  ...  This proposed smart application can provide a convenient and easy way for busy parents to take care of their babies.  ...  A hybrid memetic algorithm with back- propagation classifier for fish classification based on robust features extraction from PLGF and shape measurements.  ... 
doi:10.32628/ijsrst207161 fatcat:pwyy6knkkzeq3cbkmujqzbelqq

A Survey on Evolutionary Computation Approaches to Feature Selection

Bing Xue, Mengjie Zhang, Will N. Browne, Xin Yao
2016 IEEE Transactions on Evolutionary Computation  
Multi-Objective Feature Selection Most of the existing evolutionary multi-objective (EMO) algorithms are designed for continuous problems [244] , but feature selection is a discrete problem.  ...  on ACO for multi-objective filter feature selection.  ... 
doi:10.1109/tevc.2015.2504420 fatcat:wj2zddgcwncgtf6kphvhyd5pq4
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