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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2015“…The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
Published 2024“…The KNN and SVM algorithms were alsotrained and tested to complete the binary classification of flight delays for benchmarking purposes. …”
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Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…Next, a novel hybrid Artificial Neural Network - Quantum-Inspired Evolutionary Programming (QIEP-ANN) is developed for comparison. Later, a Least-Squares Support Vector Machine (LS-SVM) model was developed using cross-validation technique. …”
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Modeling of mechanical properties of silica fume-based green concrete using machine learning techniques
Published 2022“…ML algorithms are used to predict SFC compressive strength to promote the use of green concrete. …”
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Novel vector control method for three-stage hybrid cascaded multilevel inverter
Published 2011“…The inverter has been constructed, and the control algorithm has been implemented. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Effective gene selection techniques for classification of gene expression data
Published 2005“…Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa
Published 2020“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
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Simulation and Development of Unified Power Flow Controller Using Multilevel Inverter
Published 2010“…A comprehensive controllable UPFC using real power transfer algorithm and reactive power compensation algorithm has been successfully designed and constructed as a simulation model that is able to stabilize voltage with required power for fast changing loads.…”
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Optimization of COCOMO model using particle swarm optimization
Published 2021“…Software effort and cost estimation are crucial parts of software project development. It determines the budget, time, and resources needed to develop a software project. …”
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Development of machine learning sentiment analyzer and quality classifier (MLSAQC) and its application in analysing hospital patient satisfaction from Facebook reviews in Malaysia
Published 2022“…By manually annotating many batches of randomly chosen reviews, we constructed a machine learning quality classifier (MLQC) based on the SERVQUAL model and a machine learning sentiment analyzer (MLSA). …”
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A Hybrid Machine Learning and Optimisation-Based Model for Predicting the Success of Business-To-Consumer Software Development Projects in Indonesia
Published 2025“…Building on these findings, a predictive framework is constructed by integrating machine learning algorithms with advanced optimization and data handling strategies. …”
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Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data
Published 2023“…The algorithms are used to construct, test, and validate three categories of cybercrime threat (Malware, Social Engineering, and Password Attack) predictive models. …”
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