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using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
levels based » event based (Expand Search), models based (Expand Search)
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181
Graph Contraction for Mapping Data on Parallel Computers
Published 1994“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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182
Mapping realistic data sets on parallel computers
Published 1993“…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
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183
Parallel genetic algorithm for disease-gene association
Published 2011“…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…”
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184
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185
Particle swarm optimization algorithm: review and applications
Published 2024“…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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186
New enumeration algorithm for regular boolean functions
Published 2018“…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
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187
Empirical comparison of regression test selection algorithms
Published 2001“…These criteria are: number of selected test cases, execution time, precision, inclusiveness, preprocessing requirements, type of maintenance, level of testing, and type of approach. The empirical results show that the five algorithms can be used for different requirements of regression testing. …”
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188
The Effects of Data Mining on Small Businesses in Dubai
Published 2011“…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …”
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189
Spider monkey optimizations: application review and results
Published 2024“…Optimization algorithms are applied to find efficient solutions in different problems in several fields such as the routing in wireless networks, cloud computing, big data, image processing and scheduling, and so forth. …”
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190
A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …”
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191
An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…First, the NARXNN model acquires the data to generate a residual error vector. Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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192
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
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193
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194
Convergence behavior of the normalized least mean fourth algorithm
Published 2000“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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195
Evolutionary algorithm for predicting all-atom protein structure
Published 2011“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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196
GenDE: A CRF-Based Data Extractor
Published 2020“…If the wrapper failed to work with the new page, a new wrapper/schema would be re-generated by calling an unsupervised wrapper induction system. In this paper, a new data extractor called GenDE is proposed. It verifies the site schema and extracts data from the Web pages using Conditional Random Fields (CRFs). …”
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197
Three-phase simulated annealing algorithms for exam scheduling
Published 2003“…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
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198
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Published 2023“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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199
The effects of data balancing approaches: A case study
Published 2023“…In this article, we present a case study approach for investigating the effects of data balancing approaches. The case study concerns the discrimination between growth hormone treated and non-treated animals using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) data. …”
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200
A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS
Published 2020“…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …”
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