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Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems by Homayouni, Seyed Mahdi

“…A genetic algorithm is developed to tune the membership functions (MFs) of input variables of GDF and GSF controllers. …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…Some researchers addressed the issue of test case prioritization using Genetic Algorithm, but the authors do not select modification-revealing before prioritization and used the same fault severity. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. The approach is based on optimization of selected test case from test suite T. …”
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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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Development of genetic fuzzy logic controllers for complex production systems by Homayouni, Seyed Mahdi, Tang, Sai Hong, Ismail, Napsiah

“…Genetic algorithm is used to tune the membership functions of input variables of GSF or GDF controllers. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir by Sambo, C.H., Hematpour, H., Danaei, S., Herman, M., Ghosh, D.P., Abass, A., Elraies, K.A.

“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

“…Recently, the swarm-based hybrid algorithms have given significant performance in cancer classification. …”
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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

“…This abnormal distribution makes it difficult to obtain a consistent and balanced dataset, which can weaken the overall classification performance. 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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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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AUTOMATED GUIDED ROBOT (AGR) by Abd Rahim, Mohd Azlan Shah

“…Compared to manual mobile robots, AGRs require sensors and control systems that generate feedback for the re-evaluation of an unexpected situation and to detect obstacles in the path the AGR is required to follow. …”
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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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An experimental study of classification algorithms for crime prediction. by Iqbal, Rizwan, Azmi Murad, Masrah Azrifah, Mustapha, Aida, Panahy, Payam Hassany Shariat, Khanahmadliravi, Nasim

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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…However, the MBGWO has several issues in finding a good quality solution. Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

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Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

“…Therefore new sets of invariant algorithms have been proposed to resolve the above mentioned issues. …”
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Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

“…Evaluation was performed based on two metrics: classification accuracy and size of feature set. The results showed that the CFS-MCFA-SVM algorithm outperforms benchmark methods in terms of classification accuracy and genes subset size. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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