Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

“…Because the effective data characteristics are destroyed by the abnormal behaviors, the abnormal behaviors can be detected through comparing the difference between the reconstruction error and the detection threshold. To improve the feature extraction ability and the robustness of AE network, the sparse restrictions and the noise coding are introduced into the auto-encoder, and the hyper-parameters of AE network are optimized through the particle swarm optimization algorithm to improve the learning efficiency and generalization ability. …”
Get full text

Multi-objective performance optimization of turbofan engine for test run by WEI Bofei, WANG Yuting, GUO Zexuan, LIU Feng, XI Feng, SI Shubin, CAI Zhiqiang

“…Then, the multi-objective performance optimization model based on tree augmented naive bayes is established and compared and verified with the current mainstream algorithm for verification. …”
Get full text

Dynamic optimization of intersatellite link assignment based on reinforcement learning by Weiwu Ren, Jialin Zhu, Hui Qi, Ligang Cong, Xiaoqiang Di

“…Different from the swarm intelligence method in principle, this algorithm models the combinatorial optimization problem of links as the optimal sequence decision problem of a series of link selection actions. …”
Get full text

Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
Get full text

Quantifying and optimizing single-molecule switching nanoscopy at high speeds. by Yu Lin, Jane J Long, Fang Huang, Whitney C Duim, Stefanie Kirschbaum, Yongdeng Zhang, Lena K Schroeder, Aleksander A Rebane, Mary Grace M Velasco, Alejandro Virrueta, Daniel W Moonan, Junyi Jiao, Sandy Y Hernandez, Yongli Zhang, Joerg Bewersdorf

“…Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. …”
Get full text

YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…Replacing YOLOv8’s C2f module with C2f-DCNv3 increases the network’s ability to focus on the target region while lowering the amount of model parameters. The MSCA mechanism is added after the backbone’s SPPF module to improve the model’s detection performance by directing the network’s detection resources to the major road target detection zone. …”
Get full text

Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
Get full text

An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…Finally, it saves the loss and accuracy data during the training process and evaluates the accuracy of the model. In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
Get full text

Optimization of treatment for patients with combined unstable pelvic and thoracic injuries by О.А. Бур’янов, В.П. Кваша, В.М. Дьомін, Д.В. Мясніков, В.М. Лянскорунський

“…Its solution requires a multidisciplinary approach, and further study will allow to refine treatment strategies and improve outcomes. The purpose was to improve treatment outcomes in patients with combined injuries of the pelvis and chest by optimizing treatment algorithm. …”
Get full text

Microgrid Load Forecasting Based on Improved Long Short-Term Memory Network by Qiyue Huang, Yuqing Zheng, Yuxuan Xu

“…In this paper, a load-forecasting algorithm for microgrid based on improved long short-term memory neural network (LSTM) is proposed. …”
Get full text

Novel validity indices for dynamic clustering and an Improved Dynamic Fuzzy C-Means by Ramiro Saltos, Ignacio Carvajal, Fernando Crespo, Richard Weber

“…To illustrate the application of these novel indices, we introduce an improved version of the dynamic fuzzy c-means algorithm (I-DFCM) which offers enhanced computational stability for handling dynamic data. …”
Get full text

An Accurate Book Spine Detection Network Based on Improved Oriented R-CNN by Haibo Ma, Chaobo Wang, Ang Li, Aide Xu, Dong Han

“…This allows for a more accurate computation of anchor box aspect ratios that are better aligned with the book spine dataset, enhancing the model’s training performance. We conducted comparison experiments between the proposed model and other state-of-the-art models on the book spine dataset, and the results demonstrate that the proposed approach reaches an mAP of 90.22%, which outperforms the baseline algorithm by 4.47 percentage points. …”
Get full text

Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

“…In order to solve the problems such as mutual occlusion of leaves, light disturbance, and small lesion area under complex background, YOLO-SSM, a tea disease detection model, was proposed in this paper. The model introduces the SSPDConv convolution module in the backbone of YOLOv8 to enhance the global information perception of the model under complex backgrounds; a new ESPPFCSPC module is proposed to replace the original spatial pyramid pool SPPF module, which optimizes the multi-scale feature expression; and the MPDIoU loss function is introduced to optimize the problem that the original CIoU is insensitive to the change of target size, and the positioning ability of small targets is improved. …”
Get full text

TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. The test results of KITTI and CCTSDB2021 public traffic datasets show that compared with the original YOLOv5 model, the improved algorithm reduces the number of parameters by 20%, the calculation amount by 21%, and mAP@0.5 by 1.0%. …”
Get full text

Mobile Robot Path Planning Based on Fused Multi-Strategy White Shark Optimisation Algorithm by Dazhang You, Junjie Yu, Zhiyuan Jia, Yepeng Zhang, Zhiyuan Yang

“…A novel multi-strategy fusion white shark optimization algorithm is proposed, focusing on actual scenario requirements, to provide optimal solutions for mobile robot path planning. …”
Get full text

Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

“…Critical parameters, including stator tooth tip thickness, slot tip radius, slot height, stator yoke height, stator tooth thickness, and the number of turns per phase, were optimized to enhance efficiency. The artificial bee colony (ABC) algorithm was utilized for the first time to determine the optimal configuration of an external rotor PMSM. …”
Get full text

Shape Optimization of the Cross-Section for Noncircular Hypersonic Missile Forebody by Jingfan Chen, Xiaoqiang Fan, Bing Xiong, Yi Wang

“…The evolutionary algorithm has been utilized to improve the optimization efficiency. …”
Get full text

Heating Load Prediction with Meta-Heuristic ‎Algorithms and Adaptive Neuro-Fuzzy ‎Inference System Integration by Seyed Hadi Seyed Hatami, Reza Seifi Majdar

“…To enhance predic-tive accuracy, two meta-heuristic algorithms, the Reptile Search Algorithm (RSA) and the Flow Direction Algorithm (FDA), are seamlessly integrated into the Adaptive Neuro-Fuzzy Inference System (ANFIS) model. …”
Get full text

Dynamic contagion potential framework for optimizing infection control in healthcare by Alexandra Fedrigo, Mohamad Nassar, Jennifer Bail, Antonia Bates-Ford, Satyaki Roy

“…The framework also introduces a CP-based optimization algorithm for patient-to-unit assignments that jointly minimizes contagion risk while satisfying clinical and logistical constraints.ResultsThe framework's efficacy is validated through modular and integrated evaluations. …”
Get full text

Deep Reinforcement Learning for Optimal Replenishment in Stochastic Assembly Systems by Lativa Sid Ahmed Abdellahi, Zeinebou Zoubeir, Yahya Mohamed, Ahmedou Haouba, Sidi Hmetty

“…The Deep Q-Network (DQN) algorithm is adapted and employed to learn optimal replenishment policies over a fixed planning horizon. …”
Get full text