Machine Learning Models for Artist Classification of Cultural Heritage Sketches by Gianina Chirosca, Roxana Rădvan, Silviu Mușat, Matei Pop, Alecsandru Chirosca

“…Models start from common Faster R-CNN architectures, reinforcement learning, and vector extraction tools. …”
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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…Extensive computational experiments demonstrate that the proposed hybrid truck–RPAS system achieves notable operational improvements compared to traditional truck-only models. …”
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Techno-Economic Enhancement of Distribution Network by Optimal DG Allocation Along with Network Reconfiguration Considering Different Load Models and Levels by Chintan D. Patel, Tarun Kumar Tailor, Samyak S. Shah, Gulshan Sharma, Pitshou N. Bokoro

“…CAEL minimization by DG allocation and NR under multiple load models is addressed for the first time in this study. …”
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Load balancing method of service cluster based on mean-variance by Xiaoan BAO, Xue WEI, Lei CHEN, Guoheng HU, Na ZHANG

“…When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.…”
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Optimization design of urban rainwater and flood drainage system based on SWMM by Cao Xihan

“…Traditional drainage system design methods are no longer able to meet the complex needs of modern cities. To improve the overall performance of urban rainwater and flood drainage system, a coupling model of multiobjective optimization algorithm and rainstorm management model is constructed. …”
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Photovoltaic Module Fault Detection Technology Based on Remote Sensing Technology and Deeplabv3+ Model by Xiaowei Xu, Mingxian Liu, Yongjie Nie, Ke Wang, Wenhua Xu

“…The statistical test results showed that the improved K-means algorithm was significantly better than the traditional K-means in clustering accuracy, and its average error was only 0.008, which was much lower than the 0.035 of the traditional K-means. …”
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A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

“…Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. …”
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Applicability of elite samples in solving the traveling salesman problem by Goldberg model by Valery G. Kobak, Irma S. Rudova

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Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…The research results of this paper further improve the efficiency of the neural network model and maintain the accuracy of data, which not only meets the needs of highway subgrade detection but also promotes the application of large-scale image processing technology. …”
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An Enhanced IDBO-CNN-BiLSTM Model for Sentiment Analysis of Natural Disaster Tweets by Guangyu Mu, Jiaxue Li, Xiurong Li, Chuanzhi Chen, Xiaoqing Ju, Jiaxiu Dai

“…The improved DBO (IDBO) algorithm is then utilized to optimize the Convolutional Neural Network—Bidirectional Long Short-Term Memory (CNN-BiLSTM) model’s hyperparameters. …”
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Reliability growth model of quantum direct current electricity meter software based on optimization network by TIAN Teng, QIU Rujia, ZHAO Long, GENG Jiaqi, WANG Enhui, SUN Yu

“…Quantum direct current electricity meter is one of the important instruments in smart grid, the reliability growth model is of great significance to improve its reliability. …”
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New Channel Estimation Algorithm for Non-Sample-Spaced Channels in Fast Time-Varying OFDM System by 刘顺兰, 汪佳丽

“…The simulation results show that the bit error rate and channel mean square error of the proposed algorithm are both effectively improved.…”
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New Channel Estimation Algorithm for Non-Sample-Spaced Channels in Fast Time-Varying OFDM System by 刘顺兰, 汪佳丽

“…The simulation results show that the bit error rate and channel mean square error of the proposed algorithm are both effectively improved.…”
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An algorithm for generation of DEMs from contour lines considering geomorphic features by Xiao-Ping Rui, Xue-Tao Yu, Jin Lu, Muhammad Aqeel Ashraf, Xian-Feng Song

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Optimization Design of Multi-Blade Centrifugal Fan Based on Variable Weight PSO-BP Prediction Model and Multi-Objective Beluga Optimization Algorithm by Wenyang Jin, Jiaxuan Wang, Junyu Li, Ren Xu, Ming Zhou, Qibai Huang

“…This article proposes a prediction model and a multi-objective optimization algorithm and applies them to the optimization design of a multi-blade centrifugal fan. …”
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A Dendritic Neural Network-Based Model for Residential Electricity Consumption Prediction by Ting Jin, Rui Xu, Kunqi Su, Jinrui Gao

“…In this study, a dendritic neural network-based model (DNM), combined with the AdaMax optimization algorithm, is used to predict residential electricity consumption. …”
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Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion by Yuelong Liang, Haorui Liu, Yayu Chen

“…To solve problems such as the unstable detection performance of the sound anomaly detection of wind turbine gearboxes when only normal data are used for training, and the poor detection performance caused by the poor classification of samples with high similarity, this paper proposes a self-supervised wind turbine gearbox sound anomaly detection algorithm that fuses time-domain features and Mel spectrograms, improves the MobileFaceNet (MFN) model, and combines the Gaussian Mixture Model (GMM). …”
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Genetic algorithm application in multi-objective optimization of structural parameters and PID controller parameters on bus driver seat's suspension system by Pham Ngoc Dai

“…The elastic element's stiffness kd (N/m) and the damper's damping coefficient cd (Ns/m) are optimized by the Pareto Method with the objective function J(x) designed by the Weighted Square Sum method, and the min value of J(x) is found with the genetic algorithm (GA). A PID controller is integrated into the system to improve the working efficiency, and GA optimizes the controller parameters KP, KI, KD, and N. …”
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Algorithmic management and human-centered task design: a conceptual synthesis from the perspective of action regulation and sociomaterial systems theory by Carsten Röttgen, Britta Herbig, Tobias Weinmann, Andreas Müller

“…Based on these considerations, the main question of future research is not whether AM is good or bad for workers, but rather how work under AM can be designed to be humane. Our proposed model can guide and support researchers and practitioners in improving the understanding of the next generation of AM systems.…”
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New PSO-GWO-based model for enhancing power quality in electrical networks interconnected with photovoltaic sources by Mehdi Sanaei, Hamidreza Akbari, Zohreh Beheshtipour, Somayeh Mousavi

“…This research introduces an innovative model to enhance power quality within electrical networks interconnected with photovoltaic (PV) sources. …”
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