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1
Learning continuous functions using decision tree learning algorithms
Published 2001Get full text
masterThesis -
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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…For this purpose, a combination of Decisive Red Fox (DRF) Optimization and Descriptive Back Propagated Radial Basis Function (DBRF) classification are developed in the proposed work. …”
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3
Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
doctoralThesis -
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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions
Published 2017“…This arrangement results into nine recognition subsystems. Decisions from the nine classifiers are fused using decision-level (majority voting) scheme. …”
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Belief selection in point-based planning algorithms for POMDPs
Published 2017“…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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conferenceObject -
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…Thirty bound constrained benchmark functions are used to evaluate the performance of the proposed algorithm. …”
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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems
Published 2017“…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
11
Second-order conic programming for data envelopment analysis models
Published 2022“…Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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Android Malware Detection Using Machine Learning
Published 2024“…In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…GA is enhanced by adding a multi-objective function, which selects the best features and achieves improved fitness outcomes to explore the essential features and helps minimize dimensions, enhance the true positive rate (TPR), and lower the false positive rate (FPR). …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 2023“…The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. …”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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16
DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…Unlike standard machine learning approaches such as PCA, LDA, SVM, RF, GBM etc, DeepRaman functions independently, requiring no human interaction, and can be used to much smaller datasets than traditional CNNs. …”
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FoGMatch
Published 2019“…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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masterThesis -
18
Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO
Published 2022“…In doing so, to represent the surface properties of the electrocatalysts numerically, d-band theory-based electronic features and intrinsic properties obtained from density functional theory (DFT) calculations were used as descriptors. …”
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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems
Published 2009Get full text
doctoralThesis -
20
FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT
Published 2006“…New fuzzy aggregation functions are proposed. SE is hybridized with force directed algorithm to speed-up the search. …”
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