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361
Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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362
Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms
Published 2023“…The performance of all 15 of the algorithms is likely to deteriorate due to certain transformations, while the 4 state-of-the-art metaheuristics are less affected by transformations such as the shifting of the global optimal point away from the center of the search space. …”
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363
An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. …”
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364
On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. …”
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365
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An Efficient Tabu Search Algorithm For The Single-Machine Mean Tardiness Problem
Published 2020“…In this paper, an efficient tabu search algorithm is prepared ibr solving the singlemachine mean tardiness problem. …”
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367
A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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368
A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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369
Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem
Published 1998“…Experimental results are given to show that the proposed algorithm ran find the nearly optimal solution for the E-TSP that outperform many similar algorithms reported in the literature. …”
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370
Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP
Published 2021Get full text
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371
Effective dispatch strategies assortment according to the effect of the operation for an islanded hybrid microgrid
Published 2022“…The proposed off-grid microgrid's CO<sub>2 </sub>emissions, total net present cost (NPC), and the Levelized cost of energy (LCOE) have all been optimized. In HOMER software, all the possible dispatch algorithms were analyzed, and the power system responses and reliability study were carried out using DIgSILENT PowerFactory. …”
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372
Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…The results were obtained optimally, and we got 18 models, where each one had different high accurate outputs, that classify an individual to user and non-user. …”
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373
A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”
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374
A new tabu search algorithm for the long-term hydro scheduling problem
Published 2002“…The algorithm is based on using the short-term memory of the tabu search (TS) approach to solve the nonlinear optimization problem in continuous variables of the LTHSP. …”
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375
Net energy–cost optimization of STPV–PDRC integrated greenhouses: Balancing energy production and cooling demand under crop-specific DLI constraints
Published 2025“…An improved equilibrium optimizer (IEO) algorithm was employed to solve the multi-objective problem. …”
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376
Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms
Published 2004“…The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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377
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378
Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
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