Dialogues with Audiovisual Archives by Giulia Taurino

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Optimal Allocation Strategy for Power Quality Control Devices Based on Harmonic and Three-Phase Unbalance Comprehensive Evaluation Indices for Distribution Network by Fang ZHUO, Zebin YANG, Hao YI, Guangyu YANG, Meng WANG, Xiaoqing YIN, Chengzhi ZHU

“…Secondly, taking the global configuration effects, the total number and capacity of control devices as the optimization goals, and regarding the harmonic distortions and unbalance degrees of the nodes satisfying the standard as the constraint condition, the optimal configuration node and capacity of each device is determined by multi-objective particle swarm algorithm. Finally, an IEEE-18 node simulation model with non-ideal loads is built to verify the effectiveness and superiority of the proposed global evaluation and power quality control device configuration strategy for the comprehensive optimization of network harmonic and unbalance voltage.…”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…By integrating self-conducted experimental data and referenced datasets, a diverse experimental database was constructed. Improved algorithms, namely Asynchronous Learning Particle Swarm Optimization (AsyLnCPSO) and Hybrid Genetic Algorithm-based Particle Swarm Optimization (GA-HIDMS-PSO), were paired with LSTM neural networks to systematically evaluate their adaptability and effectiveness in predicting the performance of basalt fiber-reinforced concrete under freeze-thaw conditions. …”
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Optimized hybrid osprey with PSO control for improved VSC-HVDC-wind power integration by Abdulaziz Alkuhayli, Hany M. Hasanien

“…The research demonstrates that the Hybrid OOPSO algorithm is superior to the genetic algorithm (GA) and PSO by enhancing setup stability and allowing fast voltage regaining following different fault cases. …”
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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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Smart Energy Strategy for AC Microgrids to Enhance Economic Performance in Grid-Connected and Standalone Operations: A Gray Wolf Optimizer Approach by Sebastian Lobos-Cornejo, Luis Fernando Grisales-Noreña, Fabio Andrade, Oscar Danilo Montoya, Daniel Sanin-Villa

“…To assess performance, 100 independent runs per method were conducted, comparing GWO against particle swarm optimization (PSO) and genetic algorithms (GAs). …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…The study compares the proposed CNN-LSTM-BMO against other metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Differential Evolution (DE). …”
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Platform-independent Specification and Verification of the Standard Mathematical Square Root Function by Nikolay V. Shilov, Dmitry A. Kondratyev, Igor S. Anureev, Eugene V. Bodin, Alexei V. Promsky

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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management by Naser Rashnu, Babak Mozafari, Reza Sharifi

“…Traditional optimization techniques like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) often struggle with the nonlinear, high-dimensional nature of EV-grid interaction problems. …”
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Downhole Pressure Pulse Signal Recognition Based on SSA-CNN-LSTM by JIANG Panqin, LIU Xingbin, JIANG Zhicheng, LI Shanwen, HE Zhuang

“…It is found that the SSA-CNN-LSTM algorithm model outperforms traditional LSTM, CNN-LSTM, and PSO (particle swarm optimization) -CNN-LSTM models in terms of both fitting ability and prediction accuracy. …”
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Research on fusion prediction model of wind speed, gas and dust concentration under wind flow control in fully-mechanized heading face by Xiaoyan GONG, Hao ZOU, Zhuangzhuang LIU, Long CHEN, Haoran FU, Yuheng SUN, Hao LI, Xinyu WANG, Huming NIU

“…The sample data is preprocessed, and the differential evolution algorithm is introduced to search the node number and learning rate of the best hidden layer. …”
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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

“…Feature selection was performed using Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing, while ten machine learning models were implemented — ranging from Linear Regression and Decision Trees to Gradient Boosting, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) networks. …”
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A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

“…Using a Long Short-Term Memory (LSTM) algorithm optimized by Super SAPSO (Simulated Annealing Particle Swarm Optimization), the model forecasts server failures with improved accuracy, reducing False Alarm Rates and improving Failure Detection Rates. …”
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Analysis of Satellite and In Situ Optical Proxies for PIC and POC During GEOTRACES GP15 and GP17‐OCE Transects From the Subarctic North Pacific to the Southern Ocean by Yunhao Li, James K. B. Bishop, Phoebe J. Lam, Daniel C. Ohnemus

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Analysis of Sub-Synchronous Oscillation in Grid-Connected Wind Farm and Proposed Improved Solution by Trong Nghia Le, Chau Le Thi Minh, Phuong Nam Nguyen, Vu Nguyen Hoang Minh

“…Therefore, this paper proposes optimizing the internal control parameters of the RSC using meta-heuristic algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Ant Colony Optimization (ACO). …”
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Online Vulnerability Assessment in Cascading Failure Analysis Using an Intelligence Monitoring Model by Saber Armaghani, Zahra Moravej

“…Since load feeders and load response are considered in this paper, the mentioned problem is defined in the form of discrete-continuous optimization to determine the location and amount of necessary load removal as well as the amount of load transfer between the load buses to establish long-term voltage stability in the transmission network using discrete and continuous particle swarm algorithm. The proposed model has been simulated in the standard IEEE 57-bus test system to determine and prove the effectiveness of the proposed Special Protection Scheme for load shedding.…”
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A Self-Tuning Variable Universe Fuzzy PID Control Framework with Hybrid BAS-PSO-SA Optimization for Unmanned Surface Vehicles by Huixia Zhang, Zhao Zhao, Yuchen Wei, Yitong Liu, Wenyang Wu

“…In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. …”
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Enhanced grey wolf optimization for maximum power point tracking in photovoltaic systems with hybrid battery-supercapacitor storage by Chirine Benzazah, Najoua Mrabet, Ahmed ElAkkary, Fathallah Rerhrhaye

“…The proposed method was compared with conventional and metaheuristic optimisation techniques, including Particle Swarm Optimization, Ant Colony Optimization, and the standard Grey Wolf Optimization algorithm. …”
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Determination of Reactive RF-Sputtering Parameters for Fabrication of SiOx Films With Specified Refractive Index, for Highly Reflective SiOx Distributed Bragg Reflector by Elnaz Afsharipour, Byoungyoul Park, Cyrus Shafai

“…A statistical study and a Genetic Algorithm are implemented that can determine the deposition conditions (including oxygen partial flow and pressure) for fabricating a film with an arbitrary refractive index in the range of 1.4–4.2. …”
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