Search Results - (( _ evaluation genetic algorithm ) OR ( a classification issues algorithm ))

Genetic algorithms-based quality of service service selection in cloud computing using multilayer perceptron by Mosallanejad, Ahmad, Behjat, Amir Rajabi, Mustapha, Aida, Atan, Rodziah

“…The attribute selection method is based genetic algorithms (GA) and is designed to rank the cloud services before the attributes are being fed into a multi-layer perceptron (MLP) classification system. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

“…Balance of the combined features has not been assessed whereas it is essential to ensure one of the biometrics does not dominate accuracy performance. To overcome the issue of incompatible features to be combined, Wrapper Genetic Algorithm (GA) was implemented as the feature selection algorithm due to its ability to evaluate the features irrespective of which domain by masking the features with bit number. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). However, the process failed to state clearly the encoding strategy in its initial stage. …”
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Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz

“…Imbalanced class data is a common issue faced in classification tasks. Deep Belief Networks (DBN) is a promising deep learning algorithm when learning from complex feature input. …”
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Hybrid binary whale with harris hawks for feature selection by Alwajih, R., Abdulkadir, S.J., Al Hussian, H., Aziz, N., Al-Tashi, Q., Mirjalili, S., Alqushaibi, A.

“…The performance of the novel hybrid technique was evaluated by comparing to that of WOA, HHO, Particle Swarm Optimization (PSO), the Genetic Algorithm (GA), and the WOASAT-2. …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features by Sainin, Mohd Shamrie, Alfred, Rayner, Ahmad, Faudziah, Lammasha, Mohamed A.M

“…Multi-class imbalance shape-based leaf image features requires feature subset that appropriately represent the leaf shape.Multi-class imbalance data is a type of data classification problem in which some data classes is highly underrepresented compared to others.This occurs when at least one data class is represented by just a few numbers of training samples known as the minority class compared to other classes that make up the majority class.To address this issue in shapebased leaf image feature extraction, this paper discusses the evaluation of several methods available in Weka and a wrapperbased genetic algorithm feature selection.…”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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Optimized intrusion detection mechanism using soft computing techniques by Ahmad, iftikhar, Azween, Abdullah, Alghamdi, Abdullah, Hussain, Muhammad

“…So, Genetic Algorithm (GA) is used in the optimum selection of principal components instead of using traditional method. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

“…Instead of using traditional approach of selecting features with the highest eigenvalues such as PCA, this research applied a Genetic Algorithm (GA) to search the principal feature space that offers a subset of features with optimal sensitivity and the highest discriminatory power. …”
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Intuitive Content Management System to Preferences Template Throughout Data Collection by using Data Mining Classification of Prediction Method by Chan, Chung Hoong, M. A., Ameedeen

“…The sophisticated mathematical algorithm applies in data mining to segment data and evaluates the probability of a future event. …”
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Enhancement Of Cover Selection – Based Audio Steganography (CAS) Using Block-Based Chaotic Multi – Level Lsb (BCM– LSB) For Balanced Performance by Muhammad Harith bin Noor Azam

Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification by Navan, Farhad Pourpanah

“…To overcome the opaqueness issue, a Genetic Algorithm (GA) is used to extract fuzzy if-then rules from QFAM. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum by Wardhana, Mohammad Hadyan

“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Assignation of PSM evaluator using genetic algorithm by Yap, Suet Lee

“…The purpose of this paper is to present a design of development for Assignation of PSM Evaluator using Genetic Algorithm(APEGA)system.This is an application system that is used to assist the Faculty of Computer System and Software Engineering(FSKKP)of University Malaysia Pahang(UMP)in matching the optimum evaluators for the students in PSM presentation carnival.In the methodology part,a development model which involves with client participation is designed in order to use in the development of this project.The target user of the system is PSM coordinator who is responsible in assigning the PSM evaluator.Assignation of PSM Evaluator using Genetic Algorithm APEGA)is expected to be able in developing a well-distributed matching and overcoming the relevant constraints in an intelligent way. …”
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Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

“…Thus, a swarm-based hybrid approach is proposed for cancer classification with a new variant of the Firefly Algorithm (FA) and Correlation-based Feature Selection (CFS) filter. …”
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An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm by Arkok, Bassam, Zeki, Akram M., Othman, Roslina, Aborujilah, Abdulaziz

“…To address this issue, this paper proposes a new oversampling method that employs Genetic algorithm to generate an optimal and balanced dataset simultaneously. …”
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