Search Results - (( evolution classification modeling algorithm ) OR ( evolution optimisation based algorithm ))

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Simultaneously, news sentiment analysis techniques were used to discover the polarity of news according to each factor. From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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Finding an effective classification technique to develop a software team composition model by Gilal, A.R., Jaafar, J., Capretz, L.F., Omar, M., Basri, S., Aziz, I.A.

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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation by Muhammad ‘Afif Bin Husainiamer

B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems by Azad, Saiful, Mahmud, Mufti, Kamal Zuhairi, Zamli, Kaiser, M. Shamim, Jahan, Sobhana, Razzaque, Md Abdur

“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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