Evaluation of genetic algorithm alternatives for wind speed modeling using grey relational analysis by Hilmi Işık, Muhammet Burak Kılıç

“…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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A Talent Cultivation and Performance Evaluation Model Based on a Fuzzy Control Algorithm by Shanshan Jiang

“…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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Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

“…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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Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions by Olivér Törő, Tamás Bécsi, Szilárd Aradi, Péter Gáspár

“…The analysis conducted along two aspects emphasizes the different performance and scaling properties of the examined state estimation algorithms. …”
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Experimental Evaluation of Optimal Rate Delay and Power Allocation Algorithm in Wireless Control Networks by Muhammad Tahir, S. K. Mazumder

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Characterization of High-Speed Steels—Experimental Data and Their Evaluation Supported by Machine Learning Algorithms by Manfred Wiessner, Ernst Gamsjäger

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Personalized Analysis and Recommendation of Aesthetic Evaluation Index of Dance Music Based on Intelligent Algorithm by Jun Geng

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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis... by Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer

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Double Filter and Double Wrapper Feature Selection Algorithm for High-Dimensional Data Analysis by Hong Chen, Yuefeng Zheng

“…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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Algorithm, expert, or both? Evaluating the role of feature selection methods on user preferences and reliance. by Jaroslaw Kornowicz, Kirsten Thommes

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Comparative evaluation of multimarker algorithms for early-stage HCC detection in multicenter prospective studies by Jinlin Hou, Thomas Berg, Arndt Vogel, Teerha Piratvisuth, Jörg Trojan, Enrico N. De Toni, Masatoshi Kudo, Katarina Malinowsky, Peter Findeisen, Johannes Kolja Hegel, Wenzel Schöning, Kairat Madin, Konstantin Kroeniger, Henry Lik-Yuen Chan, Ashish Sharma

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Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions by Carlos Rodriguez-Navarro, Francisco Portillo, Isabel Robalo, Alfredo Alcayde

“…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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Three-Layer Retrieval and Self-Evaluation Classification Method Based on FastText Algorithm by Yidan Li, Huanhuan Hong, Luhong Wen

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Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation by Shan Zhu

“…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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A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment by Anagh Awal, Farsuram Pandit

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Collision Avoidance for Unmanned Surface Vehicles in Multi-Ship Encounters Based on Analytic Hierarchy Process–Adaptive Differential Evolution Algorithm by Zhongming Xiao, Baoyi Hou, Jun Ning, Bin Lin, Zhengjiang Liu

“…This study proposes an adaptive differential evolution algorithm model integrated with the analytic hierarchy process (AHP-ADE). …”
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Establishing a differential diagnosis model between primary membranous nephropathy and non-primary membranous nephropathy by machine learning algorithms by Shangmei Cao, Shaozhe Yang, Bolin Chen, Xixia Chen, Xiuhong Fu, Shuifu Tang

“…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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UAV Path Planning: A Dual-Population Cooperative Honey Badger Algorithm for Staged Fusion of Multiple Differential Evolutionary Strategies by Xiaojie Tang, Chengfen Jia, Zhengyang He

“…This design forms a two-population cooperative mechanism that enhances the balance between exploration and exploitation, thereby improving convergence accuracy. Experimental evaluations on the CEC2017 benchmark suite demonstrate the superiority of LRMHBA over 11 comparison algorithms. …”
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A Comparative Study between Different Machine Learning Algorithms for Estimating the Vehicular Delay at Signalized Intersections by Yazan Alatoom, Abdallah Al-Hamdan

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Second-order design of GNSS networks with different constraints using particle swarm optimization and genetic algorithms by Al Shouny Ahmed

“…In this research, we employed both genetic algorithms (GAs) and particle swarm optimization (PSO) to determine the optimal baselines for an observed real GNSS network with long distance baselines. …”
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