Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…Validation against real-world data demonstrates improved prediction accuracy using metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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Efficient Multiuser Computation for Mobile-Edge Computing in IoT Application Using Optimization Algorithm by Tawfiq Hasanin, Aisha Alsobhi, Adil Khadidos, Ayman Qahmash, Alaa Khadidos, Gabriel Ayodeji Ogunmola

“…Based on multiuser offloading, we proposed a bald eagle search optimization algorithm that can effectively reduce the end-end time to get fast and near-optimal IoT devices. …”
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Gradual Optimization of University Course Scheduling Problem Using Genetic Algorithm and Dynamic Programming by Xu Han, Dian Wang

“…Although various algorithms have been applied to solve the UCSP, most of the existing methods are limited to scheduling independent courses, neglecting the impact of joint courses on the overall scheduling results. …”
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Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

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Economic operation analysis of the power grid combining communication network and distributed optimization algorithm by Yi Zhifei

“…In the verification of the economic dispatch problem, the total output power of the distributed optimization algorithm reached 13594.87 MW, and the economic cost was reduced by about 23%. …”
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Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs by Li Qing-hua, Gui Wei-hua, Chen Zhi-gang

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Optimization of surface roughness for titanium alloy based on multi-strategy fusion snake algorithm. by Nanqi Li, ZuEn Shang, Yang Zhao, Hui Wang, Qiyuan Min

“…This paper proposes a milling parameter optimization method utilizing the snake algorithm with multi-strategy fusion to improve surface quality. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…The splitting-integrating method (SIM) is well suited to the inverse transformation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>T</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula> of digital images and patterns, but it encounters difficulties in nonlinear solutions for the forward transformation <i>T</i>. We propose improved techniques that entirely bypass nonlinear solutions for <i>T</i>, simplify numerical algorithms and reduce computational costs. …”
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Trajectory Similarity Algorithm Based on DTW and Trajectory Point Compression by GAO Wei, QIAN Chengyang, ZHANG Qi, XIE Hongquan

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A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

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Various optimization algorithms for efficient placement and sizing of photovoltaic distributed generations in different networks. by Ahmed A Zaki Diab, Fayza S Mahmoud, Hamdy M Sultan, Abou-Hashema M El-Sayed, Mohamed A Ismeil, Omar Makram Kamel

“…Various optimization techniques, namely Salp Swarm Algorithm (SSA), Marine Predictor Algorithm (MPA), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Seagull Optimization Algorithm (SOA), have been applied to achieve optimal allocation and sizing of RDGs in radial distributed systems (RDS). …”
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Development of algorithms for constructing two-dimensional optimal boundary-adaptive grids and their software implementation by A. E. Chistyakov, V. V. Sidoryakina, S. V. Protsenko

“…The application of such methods contributes to improving the accuracy, efficiency, and cost-effectiveness of computational algorithms.Materials and Methods. …”
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Cold Chain Logistics Path Optimization with Adaptive Speed and Hybrid Genetic Algorithm Solution by Yuhui Sun, Dazhi Pan

“…Through comparison to other algorithms in the literature, the results show that the hybrid genetic algorithm not only improves customer satisfaction, but also maintains a lower total cost, which is obviously superior when solving the complex cold chain distribution path optimization problem; further comparison and analysis of the mathematical model in this paper with the single-dimension satisfaction model reveals that under the same satisfaction constraint threshold, the model in this paper can significantly reduce the system operating cost; we also deeply discuss the influence mechanism of vehicle traveling mode and customer point sparsity radius on distribution path planning.…”
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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.…”
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Optimization and Scheduling of Integrated Energy Systems with Hydrogen-electricity Coupling Based on PKO Algorithm by Wenli QIN, Na RONG, Xingyan LIU

“…To address the problems of getting stuck in local optima and slow convergence speed during the solution process, the Pied Kingfisher Optimizer (PKO) algorithm was introduced. [Result] The model aims to minimize the total system cost as the objective function, and solves for the optimal scheduling results of the output of each energy network unit; Compared with traditional optimization algorithms, PKO has a faster convergence speed and is better able to achieve the goal of global optimal solution.…”
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Modern approaches for management patients with craniofacial tumors (literature review) by A. S. Dikarev, S. A. Vartanyan, A. A. Martirosyan

“…Craniofacial approaches sufficiently adhere to oncological principles and allow for the removal of even extensive tumors which greatly improve immediate and long-term outcomes, reliably enhancing quality of life, which is the most important task in the surgery of malignant skull base tumors. …”
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A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…This study introduces a novel approach to SaaS churn prediction using the Whale Optimization Algorithm (WOA) for feature selection. Results show that WOA-reduced datasets improve processing efficiency and outperform full-variable datasets in predictive performance. …”
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A novel solid waste instance creation for an optimized capacitated vehicle routing model using discrete smell agent optimization algorithm by Ahmed T. Salawudeen, Olusesi A. Meadows, Basira Yahaya, Muhammed B. Mu'azu

“…These challenges, in addition to the small instances reported in most literature, inspire this research to propose an improved routing scheme that takes into account real-time costs and eventually develops a novel instance based on OGWAMA's operation mode. …”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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Optimization of Rendering Parameters of Cesium 3DTiles Model Based on Differential Evolution Algorithm by Doujun Zhang, Yong Wu, Youcong Ni, Tinghuang Zhang, Chenxiang Gao

“…Cesium is an open-source 3D virtual earth engine based on WebGL and one of the most widely used 3D GIS engines. The 3DTiles rendering parameters in Cesium improve rendering efficiency but involve numerous data types and complex interdependencies, making simultaneous optimization challenging. …”
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