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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…In this research, different machine-learning algorithms such as logistic regression, random forest and naïve Bayes were tuned and tested. …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…Different classifiers were trained, validated, and tested for two different classification experiments - personalized and generalized. …”
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A genetic algorithm for testable data path synthesis
Published 2017“…We follow the allocation method with an automatic test point selection algorithm that trades off design area and delay with test quality. …”
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Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain
Published 2021“…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …”
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Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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An incremental approach for test scheduling and synthesis using genetic algorithms
Published 2017“…This paper presents a new and an efficient method for concurrent BIST synthesis and test scheduling. This method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and multiplexers. …”
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Detecting sleep outside the clinic using wearable heart rate devices
Published 2022“…We developed and tested a heart rate-based algorithm that captures inter- and intra-individual sleep differences in free-living conditions and does not require human input. …”
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A method for test scheduling using an evolutionary approach. (c2000)
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masterThesis -
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…Thirty bound constrained benchmark functions are used to evaluate the performance of the proposed algorithm. …”
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Data Generation for Path Testing
Published 2004“…We present two stochastic search algorithms for generating test cases that execute specified paths in a program. …”
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