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161
Block-Level Matching Recognition Algorithm for OpenStreetMap and Segments From High-Resolution Remote Sensing
Published 2025-01-01“…To address these issues, we propose a matching recognition algorithm that combines OpenStreetMap (OSM) data with high-resolution RS imagery. …”
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162
Parameter Estimation for Three-Phase Induction Motor Based on Performance Curves and Differential Evolution
Published 2025-01-01“…This paper introduces a novel and easy-to-implement offline parameter estimation method that eliminates the need for additional instrumentation by leveraging manufacturer performance curves and differential evolution optimization algorithm. Four equivalent circuit models are analyzed to evaluate the impact of core loss resistance and supplementary losses on estimation accuracy. …”
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163
Evaluation of genetic algorithm alternatives for wind speed modeling using grey relational analysis
Published 2025-04-01“…This study addresses the evaluation of the different fitness functions and the selection of different GA parameter sets, including population size, crossover rate, and mutation rate. …”
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164
A Talent Cultivation and Performance Evaluation Model Based on a Fuzzy Control Algorithm
Published 2024-11-01“…The study suggests a technique to quantify how firms develop and employ talent to address this issue. An algorithm called the fuzzy optimized talent cultivation engine (FOTCE) is introduced to evaluate the effectiveness of talent development. …”
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165
Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes
Published 2022-09-01“…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
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166
Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions
Published 2019-01-01“…The analysis conducted along two aspects emphasizes the different performance and scaling properties of the examined state estimation algorithms. …”
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167
Experimental Evaluation of Optimal Rate Delay and Power Allocation Algorithm in Wireless Control Networks
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168
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Double Filter and Double Wrapper Feature Selection Algorithm for High-Dimensional Data Analysis
Published 2025-01-01“…To address this issue, this study proposes a double filter and double wrapper (DFDW) feature selection algorithm for high-dimensional data. In the double filter stage, the algorithm first evaluates all features from two perspectives using two filter algorithms: ReliefF and the Pearson correlation coefficient. …”
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171
Evaluation of functional disorders in tuberculosis patients with the severe course of the disease
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172
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173
Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions
Published 2025-06-01“…A key aspect of the evaluation was the difference in testing conditions: while traditional algorithms were evaluated under multiple experimental configurations, deep learning models, due to their extremely high computational cost, were analyzed exclusively under a specific configuration consisting of a 1-s sampling rate, with harmonic content present and without applying power filters. …”
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174
Three-Layer Retrieval and Self-Evaluation Classification Method Based on FastText Algorithm
Published 2025-01-01Get full text
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175
Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation
Published 2022-01-01“…This paper proposes a decision tree structure, which is similar to the overall scoring process of raters, and uses the Interactive Dicremiser version 3 (ID3) algorithm to build a comprehensive evaluation decision tree for pitch, rhythm, intonation, speech rate, and emotion indicators. …”
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176
A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment
Published 2024-09-01Get full text
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177
An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration
Published 2025-04-01“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
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178
Collision Avoidance for Unmanned Surface Vehicles in Multi-Ship Encounters Based on Analytic Hierarchy Process–Adaptive Differential Evolution Algorithm
Published 2024-11-01“…This study proposes an adaptive differential evolution algorithm model integrated with the analytic hierarchy process (AHP-ADE). …”
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179
Establishing a differential diagnosis model between primary membranous nephropathy and non-primary membranous nephropathy by machine learning algorithms
Published 2024-12-01“…Context Four algorithms with relatively balanced complexity and accuracy in deep learning classification algorithm were selected for differential diagnosis of primary membranous nephropathy (PMN).Objective This study explored the most suitable classification algorithm for PMN identification, and to provide data reference for PMN diagnosis research.Methods A total of 500 patients were referred to Luo-he Central Hospital from 2019 to 2021. …”
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180