Optimizing the Hexagonal Fuzzy Transportation Problem With the Novel Dhouib-Matrix-TP1 Method by Souhail Dhouib, Aida Kharrat, Taicir Loukil, Habib Chabchoub

“…Transportation Problem (TP) is considered a combinatorial optimization problem, and its aim is to minimize the total transportation cost from several sources to different destinations. …”
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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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Optimization Method for Centralized Transmission of Offshore Wind Power from Multiple Wind Farms by Sheng LIU

“…Symmetric monopole systems and symmetrical bipolar systems should adopt different calculation methods based on system characteristics. …”
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Hybrid Optimization Method for Social Internet of Things Service Provision Based on Community Detection by Bahar Allakaram Tawfeeq, Amir Masoud Rahmani, Abbas Koochari, Nima Jafari Navimipour

“…Addressing these challenges requires efficient optimization methods. Traditional optimization algorithms have strengths and weaknesses. …”
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Optimization of Filter-aided Sample Preparation Method Based on High-resolution Mass Spectrometry by Ying ZHANG, Xuan SUN, Ling-jie MENG

“…Moreover, the improved FASP method shows no bias for identifying proteins with different molecular weights and isoelectric points, and its optimal protein loading is determined to be 20 μg. …”
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NEW WAVEGUIDE METHOD FOR DIELECTRIC PARAMETER MEASUREMENT by Andrey D. Grigoriev

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An Integrated Optimization Method for Energy-efficient Control of Hybrid Trains Considering Energy Management by Dalei HA, Wei HAN, Jinsong GUO, Zhuang XIAO, Qingyuan WANG

“…For train operation processes with characteristic of spatial segmentation, continuous state variables and different constraints, the integrated model was converted into a multi-stage hybrid train energy management and operation optimization strategy model, and then the adaptive Pseudo-spectrum method was introduced for solving the multi-stage model. …”
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Application of a dynamic optimization-based multi-attribute fusion method for fault detection. by Chen Ma, Handong Huang, Youcai Tang, Suo Cheng, Chao Wang, Xin Wang

“…To address these challenges, this study proposed a multi-attribute optimal surface-based fracture identification technology based on forward simulation records. …”
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A General Approximation Method for a Kind of Convex Optimization Problems in Hilbert Spaces by Ming Tian, Li-Hua Huang

“…Based on Jung’s method (2011), we propose a general approximation method and prove the strong convergence of our algorithm to a solution of the above optimization problem. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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Optimization Study of Gear Oil-air Lubrication Parameters Based on Orthogonal Test Method by Chang Lu, Qi Chen, Qingwei Hou, Zhaqiang Tang

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Research on pedestrian trajectory prediction method based on social attention mechanism by Linhui LI, Bin ZHOU, Jing LIAN, Yafu ZHOU

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Design of Rotors in Centrifugal Pumps Using the Topology Optimization Method and Parallel Computing in the Cloud by Xavier Andrés Arcentales, Danilo Andrés Arcentales, Wilfredo Montealegre

“…This work aims to develop a parallelized computational algorithm in MATLAB version R2020a to design the rotor of a radial flow in a centrifugal pump using the finite-element method (FEM), topology optimization method (TOM), and parallel cloud computing (bare-metal vs. virtual machine). …”
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A novel rapid and reproducible flow cytometric method for optimization of transfection efficiency in cells. by Stefanie Homann, Christian Hofmann, Aleksandr M Gorin, Huy Cong Xuan Nguyen, Diana Huynh, Phillip Hamid, Neil Maithel, Vahe Yacoubian, Wenli Mu, Athanasios Kossyvakis, Shubhendu Sen Roy, Otto Orlean Yang, Theodoros Kelesidis

“…By using optimized ratios of transfection reagent and a nucleic acid (DNA or RNA) vector directly labeled with a fluorochrome, this method can be used as a tool to simultaneously quantify cellular toxicity of different transfection reagents, the amount of nucleic acid plasmid that cells have taken up during transfection as well as the amount of the encoded expressed protein. …”
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Optimization method of truss structure size and shape based on harmonic search genetic algorithm by XIE Jun, ZHANG Huashuai, LIN Shuqin, PANG Bolei, YAN Jie

“…Compared with genetic algorithm (GA), heuristic particle swarm optimization (HPSO) and other optimization algorithms, the optimization effect is obvious, and it is a method suitable for the shape optimization of truss structure.…”
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Optimization Method for Transit Signal Priority considering Multirequest under Connected Vehicle Environment by Song Xianmin, Yuan Mili, Liang Di, Ma Lin

“…Aiming at reducing per person delay, this paper presents an optimization method for Transit Signal Priority (TSP) considering multirequest under connected vehicle environment, which is based on the travel time prediction model. …”
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Research on the Bearing Remaining Useful Life Prediction Method Based on Optimized BiLSTM by Yi Zou, Wenlei Sun, Tiantian Xu, Bingkai Wang

“…Afterward, multi-domain features are extracted and evaluated using different metrics. The optimal degradation feature is then selected. …”
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Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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Optimization of Wear Process Parameters of Al6061-Zircon Composites Using Taguchi Method by R. Vijayakumar, J. S. Srikantamurthy, Shanawaz Patil, S. Rudresha, A. Manjunatha, T. Hemanth Raju, A. Haiter Lenin

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A Storm Frame Optimization Method for Predicting and Warning the Safety Status of a Shearer by Pei Zhang, Yanpeng He, Li Ma, Changkui Cong

“…Finally, the optimized GRU model is embedded into the optimized Storm framework to achieve real‐time prediction and early warning of different dimensional data of the shearer. …”
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