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181
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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182
Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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183
Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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184
A New Penalty Function Algorithm For Convex Quadratic Programming
Published 2020“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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185
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Among these, K-means is widely used for efficiently solving clustering problems. …”
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masterThesis -
186
A Scatter search algorithm for exam scheduling. (c2006)
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masterThesis -
187
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188
Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques
Published 2024“…The DinoLite Microscope’s high-resolution images are used to measure the length and width of wheat anthers. …”
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189
Second-order conic programming for data envelopment analysis models
Published 2022“…Data envelopment analysis (DEA) is a widely used benchmarking technique. …”
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190
Revolutionizing sustainable supply chain management: A review of metaheuristics
Published 2023“…The paper also identifies the key factors that influence the success of using metaheuristics for SSCM, such as the choice of algorithm, problem complexity, and data quality. …”
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191
Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction
Published 2025“…While the threshold for blockers is defined as ≤10 μ M and for non-blockers, it is >10 μ M, our analysis indicates that a threshold of 60- 80 μ M provides a more accurate cut-off for non-blockers. …”
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192
Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
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193
The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Recent advances in algorithm design have shown a growing interest in seeking exact solutions to many hard problems. …”
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conferenceObject -
194
An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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195
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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196
An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…We use an ant colony optimization algorithm in the adaptation process. …”
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197
Multi-marker-LD based genetic algorithm for tag SNP selection
Published 2014“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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198
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199
A Recommended Replacement Algorithm for the Scalable Asynchronous Cache Consistency Scheme
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conferenceObject -
200
Convergence and steady-state analysis of the normalized least mean fourth algorithm
Published 2007“…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …”
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