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Two-stage Community Discovery Algorithm for Multi-point Seed Prepartition
Published 2021-08-01“…First,high-impact nodes in the network are identified,and high-impact nodes are aggregated using the k-means algorithm to obtain high-impact community clusters. …”
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222
A Dynamic State Cluster-Based Particle Swarm Optimization Algorithm
Published 2025-08-01Get full text
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223
Modelling Land-use Changes using MDC, MD and ML Algorithms (Case Study: Midawood-Dalon Watershed)
Published 2025-02-01Get full text
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224
BiModalClust: Fused Data and Neighborhood Variation for Advanced K-Means Big Data Clustering
Published 2025-01-01“…K-means clustering is a fundamental tool in data mining, yet its scalability and efficacy decline when faced with massive datasets. …”
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225
K-Means++ Clustering-Based Approach for SDN Controller Placement in LEO Satellite Networks
Published 2025-01-01Subjects: Get full text
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226
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A clustering algorithm based on grids for core data and adjacency relationships for edge data
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228
Particle Swarm Optimization Algorithm for Determining Global Optima of Investment Portfolio Weight Using Mean-Value-at-Risk Model in Banking Sector Stocks
Published 2024-12-01“…The novelty of this research lies in developing an accurate computational algorithm for determining the global optima of mean-value-at-risk portfolio investments, yielding precise, consistent results with relatively fast computation times. …”
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Research on Rolling Bearing Fault Diagnosis Method Based on MPE and Multi-Strategy Improved Sparrow Search Algorithm Under Local Mean Decomposition
Published 2025-04-01“…To address the issues of non-stationarity, noise interference, and insufficient discriminative power of traditional fault feature extraction methods in rolling bearing vibration signals, this paper proposes a fault diagnosis method based on multi-scale permutation entropy (MPE) and a multi-strategy improved sparrow search algorithm (MSSA) under local mean decomposition (LMD). …”
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231
New management grading for pig farms: management grading system using pig carcass weight, back fat thickness and k-means algorithm
Published 2025-02-01“…Methods A total of 48,298 pigs were grouped (A, B, C, D group) using the k-means algorithm, carcass weight and backfat thickness. …”
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232
Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model
Published 2025-01-01“…Further, the pre-processed image is given to the segmentation process, where the Adaptive Fuzzy C-Means (AFCM) technique is utilized. Meanwhile, the parameters of the AFCM algorithm complicate the cluster assignment in the presence of outliers or noise, thus resulting in reduced clustering performance. …”
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233
Research on Automatic Tracking and Size Estimation Algorithm of “Low, Slow and Small” Targets Based on Gm-APD Single-Photon LIDAR
Published 2025-01-01Subjects: Get full text
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234
A Geometric Mean of Parameterized Arithmetic and Harmonic Means of Convex Functions
Published 2012-01-01“…A new algorithmic self-dual operator for convex functions named “the geometric mean of parameterized arithmetic and harmonic means of convex functions” is proposed, and its essential properties are investigated.…”
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235
YOLOrot2.0: A novel algorithm for high-precision rice seed size measurement with real-time processing
Published 2024-12-01“…Experimental results demonstrate that YOLOrot2.0 achieves an mAP (mean average precision) score of 0.95, surpassing other comparative algorithms. …”
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Analyzing the Problems of Ayandeh Bank Branches across the Country Using Data Mining Technique
Published 2014-06-01Subjects: Get full text
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238
A Clustering-based Simulated Annealing Algorithm with Taguchi Method for the Discrete Ordered Median Problem
Published 2022-02-01“…For that purpose, we proposed a Simulated Annealing (SA) metaheuristic with K-means Clustering Algorithm in initialization for the DOMP. …”
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239
Estimation and Assessment of Partial Shading Patterns in Large PV Farms Using ANN Algorithm
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240
A law of meaning
Published 2025-01-01“…This article rejects the canonical ideal of a one-to-one correspondence between meaning and marker and proposes a set-theoretical and optimality-based law for the relationship between meaning and its markers which allows for distinguishing true markers (such as not, no, never for negation) from otherwise associated items (such as negative polarity items as but, any): a meaning is expressed by the set of non-randomly recurrent markers that together are the best collocation of that meaning. …”
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