Search Results - (( based optimization based algorithm ) OR ( time evaluation tree algorithm ))
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…In conclusion, the hybrid algorithm based solution strategies improved efficiency with convincing results, therefore, this will assist planners for better decision making to optimize area to achieve more trees to be planted. …”
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Thesis -
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image
Published 2024“…This thesis presents a local-based stereo matching algorithm to increase the accuracy on complex regions. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree
Published 2021“…The proposed algorithm is used to fetch relevant features based from the high-dimensional input feature space. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…Quantitative analysis highlights China’s prominent contributions to the field, while the thematic analysis reveals three key findings: (1) optimization methods based on intelligent algorithms such as NSGA-II, artificial neural networks, and gradient-boosted decision trees significantly enhance computational efficiency; (2) dynamic simulation integrated with lifecycle assessment enables a more comprehensive evaluation of building performance; and (3) climate-adaptive strategies improve building resilience to future climate uncertainties. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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9
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…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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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…Traditional methods often rely on expert visual assessments, which are labour-intensive, subjective, and time-consuming. The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Energy efficiency mechanism using mobile-based fermat's spiral in wireless sensor networks
Published 2011“…We evaluated the performance of wireless sensor network using minimum spanning tree algorithm specifically Prim’s Algorithm in order to know the bottleneck effect on wireless sensor network and propose a better solution performance based on Fermat Spiral model. …”
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Proceeding Paper -
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Disparity map algorithm for stereo matching process using local based method
Published 2022“…Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. …”
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Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…Machine learning model selection is an iterative process of exploring, evaluating, and improving algorithms. Selecting an optimal model for a particular domain is rigid, challenging, and complicated. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…As well as, evaluate Coalition-Based Index-Tree framework in terms of the number of traversed nodes, space-cost overhead, and index building-time. …”
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The Transformer model with transferred weights outperformed models trained from scratch using supervised learning. To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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