Search Results - (( variable optimization mining algorithm ) OR ( evolution classification _ algorithm ))

Mine blast algorithm for optimization of truss structures with discrete variables by Sadollah, Ali, Bahreininejad, A., Eskandar, Hadi, Abd Shukor, Mohd Hamdi

“…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Using Pattern Search Methods for Minimizing Clustering Problems by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June, Mohagheghtabar, Maryam

“…Recently, the problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization,and an algorithm for solving the cluster analysis problem based on nonsmooth optimization techniques is developed. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…This optimization problem has a number of characteristics that make it challenging: it has many local minimum, the optimization variables can be either continuous or categorical, and there are no exact analytical derivatives. …”
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Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

“…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

“…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…Individual emotional states are highly variable and are subject to evolution from personal experiences. For this reason, the above system is designed to be able to perform learning and classification in real-time to account for inter-individual and intra-individual emotional drift over time. …”
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