Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives by Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao

“…We separate ProMPs as Gaussians at each timestep and minimize Kullback–Leibler (KL) divergence, with a gradient ascent–descent algorithm performed to obtain optimized ProMPs. Given optimized ProMPs, we outline a unified robot movement adaptation method for extending from a single obstacle to multiple obstacles. …”
Get full text

A Hybrid Particle Swarm Optimizer for Curriculum Sequencing Problem by Xianjie Peng, Xiaonan Sun, Zhen He

“…The numerical comparison experiments show that the proposed algorithm is effective in solving function optimization in comparison to several popular PSO variants; furthermore, for the optimization of the designed curriculum sequencing problem, the proposed algorithm shows significant advantages over the compared algorithms with respect to the degree of the satisfaction of the objectives, i.e., 20, 14, and 5 percentages higher, respectively.…”
Get full text

Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…This enhancement aims to improve the accuracy of reservoir modeling outcomes in reproducing real data. …”
Get full text

On the implementation of a global optimization method for mixed-variable problems by Nannicini, Giacomo

“…We propose several modifications aimed at generalizing and improving these two algorithms: (i) the use of an extended space to represent categorical variables in unary encoding; (ii) a refinement phase to locally improve a candidate solution; (iii) interpolation models without the unisolvence condition, to both help deal with categorical variables, and initiate the optimization before a uniquely determined model is possible; (iv) a master-worker framework to allow asynchronous objective function evaluations in parallel. …”
Get full text

Offline Magnetometer Calibration Using Enhanced Particle Swarm Optimization by Lei Huang, Zhihui Chen, Jun Guan, Jian Huang, Wenjun Yi

“…First, a magnetometer calibration model is established. Second, the DAEPSO algorithm is employed to fit the ellipsoid parameters. …”
Get full text

Highly Precise Time Compensation Algorithm for Synchronous Communication System Based on Least Squares by Jin Su, Changshui Li, Qingbo Liu, Sheng Zhao, Xiangyu Wang

Get full text

Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions by Carlos Rodriguez-Navarro, Francisco Portillo, Isabel Robalo, Alfredo Alcayde

“…The selection of the optimal NILM algorithm for real-world applications must consider a balance between desired accuracy, load types, electrical signal characteristics, and crucially, the limitations of available computational resources.…”
Get full text

USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…To address these issues, we propose a specialized algorithm named Unmanned-system Small-object Detection-You Only Look Once (USD-YOLO). …”
Get full text

Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway by Wenliang Zhou, Junli Tian, Jin Qin, Lianbo Deng, TangJian Wei

“…And its heuristic algorithm is designed to optimize the multiperiod mixed train schedule beginning with generating an initial solution by scheduling all types of train type by type and then repeatedly improving their periodic schedules until the objective value cannot be reduced or the iteration number reaches its maximum. …”
Get full text

Retrieval Augmented Therapy Suggestion for Molecular Tumor Boards: Algorithmic Development and Validation Study by Eliza Berman, Holly Sundberg Malek, Michael Bitzer, Nisar Malek, Carsten Eickhoff

Get full text

Research on Efficiency of Hybrid Power System and Optimization of Control Strategy by Hongyu Zhu, Peng Hao, Guozhi Liu, Wei Xu, Haisheng Xu

“…The results show that the efficiency optimization algorithm can effectively improve the comprehensive system efficiency of the power system and reduce the fuel consumption of the vehicle.…”
Get full text

Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…The developed sigmoid (SG) activation function-based ELM (SG-ELM) shows performance improvement over sine (SI) function-based ELM (SI-ELM) model and PS-SVR model with an improvement of 79.25 % and 89.4 % using root mean square error (RMSE) performance measuring parameter. …”
Get full text

Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…To address this shortcoming, we studied AR subtask offloading and resource allocation in a multi-hop, multi-access edge computing federation. Our approach improves the quality of experience (QoE) by optimizing video quality and reducing delay while ensuring fairness, which is modeled as the ratio between provided and required quality. …”
Get full text

Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
Get full text

Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

Get full text

Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions by Guo Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang

“…Aiming to improve the treatment of multiphase pollutants, this study builds a three-objective optimization model by considering the optimization of treatment effect, energy consumption, and an innovatively constructed optimization objective of direct and indirect carbon emissions. …”
Get full text

An optimal federated learning-based intrusion detection for IoT environment by A. Karunamurthy, K. Vijayan, Pravin R. Kshirsagar, Kuan Tak Tan

“…The Chimp optimization algorithm is used in the proposed work to select optimal features. …”
Get full text

Enhancing mass vaccination programs with queueing theory and spatial optimization by Sherrie Xie, Maria Rieders, Srisa Changolkar, Bhaswar B. Bhattacharya, Elvis W. Diaz, Michael Z. Levy, Michael Z. Levy, Ricardo Castillo-Neyra, Ricardo Castillo-Neyra

“…Queueing theory offers a framework for modeling queue formation at vaccination sites and its effect on vaccine uptake.MethodsWe developed an algorithm that integrates queueing theory within a spatial optimization framework to optimize the placement of mass vaccination sites. …”
Get full text

RELIABILITY ESTIMATION OF MECHANICAL SEALS BASED ON ARTIFICIAL HUMMINGBIRD ALGORITHM AND THREE⁃PARAMETER WEIBULL DISTRIBUTION by LI AnHong, ZHU JunHua, YU Ling

“…In order to quickly and accurately evaluate the reliability of mechanical seals,the three⁃parameter Weibull distribution was used to model the mechanical seal failure data.The reliability evaluation problem of mechanical seal was transformed into a constraint optimization problem,and a reliability evaluation method based on artificial hummingbird algorithm(AHA)was proposed.Through numerical simulation and case analysis,maximum likelihood estimation(MLE),improved Harris Hawks optimization(IHHO)algorithm and AHA were used to compare calculation accuracy and operational efficiency in solving the Weibull distribution parameter estimation problems.The results show that the parameter estimation using AHA has advantages of faster convergence speed and higher accuracy,and it can shorten the optimization time and improve the accuracy compared with MLE algorithm and IHHO algorithm,which provides a new and efficient method for Weibull parameter estimation of mechanical seals.…”
Get full text

Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
Get full text