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Boosting the visibility of services in microservice architecture
Published 2023“…These assessments can be performed by means of a live health-check service, or, alternatively, by making a prediction of the current state of affairs with the application of machine learning-based approaches. In this research, we evaluate the performance of several classification algorithms for estimating the quality of microservices using the QWS dataset containing traffic data of 2505 microservices. …”
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Predicting Plasma Vitamin C Using Machine Learning
Published 2022“…<p dir="ltr">Precision Nutrition makes use of personal information about individuals to produce nutritional recommendations that have more utility than general population level recommendations. …”
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand in the short term. …”
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Improvement Algorithm for Limited Space Scheduling
Published 2001“…The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.…”
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Decision-level Gait Fusion for Human Identification at a Distance
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Artificial neural network algorithms. (c1999)
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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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Formal synthesis of VLSI layouts from algorithmic specifications
Published 2020“…In this paper we present a formal approach for high level synthesis. This formal high level syntesis system uses recursive algorithms to model the behaviour to be synthesized. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…While research in ASD diagnosis is evolving through the application of machine learning (ML) techniques, practical implementation in clinical settings has not progressed at the same pace. …”
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A genetic algorithm for testable data path synthesis
Published 2017“…The approach is formulated as an allocation problem and solved using an efficient genetic algorithm that generates cost-effective testable designs. …”
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A neural networks algorithm for data path synthesis
Published 2003“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks
Published 2012“…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers
Published 2023“…<p dir="ltr">This article proposes a digital twin (DT)-based diagnosis and fault-tolerant control for T-type three-level rectifiers. To develop the DT, a dense deep neural network (DNN) machine learning approach is used. …”
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A comparative study of five regression testing algorithms
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
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Adaptive Chip-Level Channel Estimation for IMT-DS System: DL and UL
Published 2005“…In this paper, chip-level adaptive channel estimation has been explored by using LMS algorithm for wideband CDMA channel estimation. …”
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A simplified sliding‐mode control method for multi‐level transformerless DVR
Published 2022“…<p dir="ltr">Here, a finite-control-set sliding-mode control (FCS-SMC) method is proposed for single-phase three-level T-type inverter-based transformerless dynamic voltage restorers (TDVRs). …”