Search Results - candidate ((((prediction algorithm) OR (optimization algorithm))) OR (detection algorithm))
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1
Breast Cancer Prediction Model Using Machine Learning
Published 2021“…Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…The algorithm is improved with Particle Swarm Optimization that trains three different supervised classifiers. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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Thesis -
4
Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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Proceeding Paper -
6
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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Thesis -
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A Novel Model on Curve Fitting and Particle Swarm Optimization for Vertical Handover in Heterogeneous Wireless Networks
Published 2015“…This study uses two modules that utilize the particle swarm optimization (PSO) algorithm to predict and make an intelligent vertical handover decision. …”
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Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…In this study, the performances of four different peak models of time domain approach which are Dumpala's, Acir's, Liu's, and Dingle's peak models are evaluated for electroencephalogram (EEG) signal peak detection algorithm. The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
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Conference or Workshop Item -
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Adaptive DNA computing algorithm by using PCR and restriction enzyme
Published 2004“…By doing this, the molecules which serve as a solution candidate can he narrowcd down and the optimal solution can be detected easily. …”
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Book Section -
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Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The algorithms were examined on two real datasets, namely, NSL-KDD and Landsat. …”
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12
Dynamic modelling of proton exchange membrane fuel cell system for electric bicycle / Azadeh Kheirandish
Published 2016“…Recent models provide high accuracies using complex systems and complicated calculations using advanced optimization algorithms. However, designing an accurate dynamic model for prediction and controlling the system in a real time condition is a challenge in this field. …”
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Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network
Published 2016“…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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Defect green coffee bean detection using image recognition and supervised learning
Published 2022“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Academic Exercise -
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A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…The algorithm will select the minimum path from the candidate points to target while avoiding obstacles. …”
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Evaluating critical success factors in AI-driven drug discovery using AHP: a strategic framework for optimization
Published 2025“…The framework comprises six key criteria: Data Quality and Management (DQM), Algorithm Performance and Optimization (APO), Interpretability and Explainability (IE), Regulatory Compliance and Ethical Considerations (RCEC), Computational Efficiency and Scalability (CES), and Validation and Experimental Confirmation (VEC). …”
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Intelligent surveillance system for street surveillance
Published 2017“…For the tracking algorithm, the effectiveness between colour, edge and texture features for target and candidate blobs were analysed. …”
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Intelligent surveillance system for street surveillance
Published 2017“…For the tracking algorithm, the effectiveness between colour, edge and texture features for target and candidate blobs were analysed. …”
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An effective source number enumeration approach based on SEMD
Published 2022“…Finally, the back propagation (BP) neural network is used to predict the number of sources. Experiment shows that SEMD can effectively restrain the end effect, and the source number enumeration algorithm based on SEMD has a higher correct detection probability than others.…”
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