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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…An Intrusion Detection System is software or application which is used to detect thread, malicious activities and the unauthorized access to the computer system and warn the administrators by generating alarms. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size by Kunalan D., Krishnan P.S., Permal N.

Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

Extraction and Optimization of Fuzzy Protein Sequences Classification Rules Using GRBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

“…Traditionally, two protein sequences are classified into the same class if their feature patterns have high homology. These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Results have shown that integrated Cuckoo search and induced SVM learning algorithm produced the best-selected feature subset with 99% coefficient of determination, lowest RMSE and MAE of 0.081 and 0.0132 respectively.…”
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Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

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Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network by Shengsheng, Qin, Zhipeng, Cao, Feng, Wang, Ngu, Sze Song, Kho, Lee Chin, Hui, Cai

“…The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
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A Data Mining Approach to Enhancing Birth and Death Registration Processes by Erfan, Hasmin

“…The optimal number of clusters of clusters for birth and death data is determined as three using elbow and silhouette validation methods. …”
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Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Arabic handwriting recognition is a dynamic and stimulating field of study within pattern recognition. This system plays quite a significant part in today's global environment. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Machine Learning Approach Regarding The Classification And Prediction Of Dog Sounds: A Case Study Of South Indian Breeds by Prabu Mohandas, Jerline Sheebha Anni, Khairunnisa Hasikin, Dhayalan Velauthapillai, Veena Raj, Thanihaichelvan Murugathas, Rajkumar Thanasekaran, Muhammad Mokhzaini Azizan

Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

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Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

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