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601
FoGMatch
Published 2019“…Our solution consists of (1) two optimization problems, one for the IoT devices and one for the fog nodes, (2) preference functions for both the IoT and fog layers to help them rank each other on the basis of several criteria such latency and resource utilization, and (3) centralized and distributed intelligent scheduling algorithms that consider the preferences of both the fog and IoT layers to improve the performance of the overall IoT ecosystem. …”
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masterThesis -
602
Transformations for Variants of the Travelling Salesman Problem and Applications
Published 2017Get full text
doctoralThesis -
603
Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates
Published 2022“…<h2>Purpose</h2> <p>We present an approach that combines finite element analysis and genetic algorithms to find the optimal configuration of local resonators created in the host structure to suppress their vibration in a target low-frequency range. …”
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604
Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Published 2021“…In addition, this review analyzes recent automatic architecture optimization algorithms for DL-based PVPF. Next, the notable DL technologies are thoroughly described. …”
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605
UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. …”
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606
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607
A Stochastic Newton-Raphson Method with Noisy Function Measurements
Published 2016“…This article proposes a novel recursive algorithm providing optimal iterative-varying gains associated with the NR method. …”
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article -
608
A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
Published 2025“…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. …”
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609
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610
Scatter search for homology modeling
Published 2016“…These candidates undergo evolutionary operations that combine search intensification and diversification over a number of iterations. The metaheuristic optimizes the initial poor alignments and uses fitness functions. …”
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conferenceObject -
611
Scatter search metaheuristic for homology based protein structure prediction. (c2015)
Published 2015“…To improve homology based PSP, we propose a scatter search (SS) metaheuristic algorithm. Our algorithm optimizes the initial poor alignments, generated by a dynamic programming method. …”
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masterThesis -
612
Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids
Published 2019“…The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total demand of regular loads and EV charging. The planning algorithm specifies optimal locations and sizes of the EV charging stations and DG units that minimize two conflicting objectives: (a) deployment and operation costs and (b) associated green house gas emissions, while satisfying the microgrid technical constraints. …”
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613
A method for data path synthesis using neural networks
Published 2017“…A sequential simulator was implemented for the proposed algorithm on a Linux Pentium PC under X Windows. Several circuits hare been attempted, all yielding sub-optimal solutions.…”
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conferenceObject -
614
Minimizing Mean Tardiness Subject To Unspecified Minimum Number Tardy For A Single Machine
Published 2020“…It also uses an insertion algorithm which determines the optimal mean tardiness once the subset of tardy jobs is specified. …”
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615
One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy
Published 2020“…In this paper the one-machine scheduling problem with the objective of minimizing the mean tardiness subject to maintaining a prescribed number of tardy jobs is analysed An algorithm for solving this problem is presented. It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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article -
616
Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
Published 2017Get full text
doctoralThesis -
617
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
Published 2023Get full text
doctoralThesis -
618
One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy
Published 2020“…In this paper the one-machine scheduling problem with the objective of minimizing the mean tardiness subject to maintaining a prescribed number of tardy jobs is analysed An algorithm for solving this problem is presented. It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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619
LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…The k-fold cross-validation and grid search optimization methods were used with the LDSVM model to classify leukemia in patients and comparatively analyze their impacts. …”
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620
Determining Dominant Wind Directions
Published 2020“…Important properties of the problem are discussed and a convergent solution algorithm is designed. The algorithm could yield local optimal solutions. …”
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