Research on the Bearing Remaining Useful Life Prediction Method Based on Optimized BiLSTM by Yi Zou, Wenlei Sun, Tiantian Xu, Bingkai Wang

“…To solve these problems, a bearing RUL prediction method based on early degradation detection and optimized BiLSTM is proposed: an optimized VMD combined with the Pearson correlation coefficient is used to denoise the bearing signal. …”
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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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A Hierarchical Planning Method for AUV Search Tasks Based on the Snake Optimization Algorithm by Zhiwen Wen, Zhong Wang, Xiangdong Wen, Chenxi Niu, Pei Wang, Daming Zhou

“…This method decomposes the search task problem into a three-level programming problem, with the outer task planning goal of achieving the shortest encounter time between AUV and dynamic targets; the goal of task planning in the middle layer is to achieve the shortest actual navigation time for AUVs under different operating conditions; and the internal task planning is responsible for considering the comprehensive trajectory optimization under navigation constraints such as threat zone, path length, and path smoothness. …”
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Distribution characteristics of microbial aerosols and optimization of protective methods during ultrasonic scaling procedure by Menghan Chen, Jinjing Guo, Xiaobing Pang, Jianying Feng, Sheng Zheng

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Research on Constraint Processing Method of High-dimensional Optimization Operation Problem of Cascade Reservoirs by Zhongzheng HE, Shuliang LI, Wei HUANG, Feng YAN, Jisi FU, bin XIONG

“…The results of the correlation analysis indicated that: 1) the nested DPSA–POA intelligent algorithm combined with a penalty function can address the high-dimensional optimization problem under varying water inflow conditions using three constraint processing methods; 2) Of the three constraint processing methods, method 2, which involves DE optimization after securing a feasible solution through nested optimization, achieves the highest convergence accuracy, though the computation time is approximately 10 h; method 3, which involves DPSA–POA optimization after securing a feasible solution through nested optimization, achieves the second highest convergence accuracy, with a computation time of about 1～3 h; 3) Existing SF, SR, PF, and EC constraint treatment strategies fail to consistently converge to a feasible solution under different water inflow conditions, and the convergence accuracy of the results, upon obtaining a feasible solution, is significantly lower than that of the method introduced in this study. …”
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A Small-Sample Scenario Optimization Scheduling Method Based on Multidimensional Data Expansion by Yaoxian Liu, Kaixin Zhang, Yue Sun, Jingwen Chen, Junshuo Chen

“…Firstly, based on spatial correlation, the daily power curves of PV power plants with measured power are screened, and the meteorological similarity is calculated using multicore maximum mean difference (MK-MMD) to generate new energy output historical data of the target distributed PV system through the capacity conversion method; secondly, based on the existing daily load data of different types, the load historical data are generated using the stochastic and simultaneous sampling methods to construct the full historical dataset; subsequently, for the sample imbalance problem in the small-sample scenario, an oversampling method is used to enhance the data for the scarce samples, and the XGBoost PV output prediction model is established; finally, the optimal scheduling model is transformed into a Markovian decision-making process, which is solved by using the Deep Deterministic Policy Gradient (DDPG) algorithm. …”
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Optimizing Circular MIMO Array Imaging Using Partial Equivalent Method for Sidelobe Suppression by Yiming Dai, Zhikun Zheng, Hong Ye, Xu Zhang, Jun Yang, Guangsheng Deng, Ying Li, Zhiping Yin

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Genomic selection optimization in blueberry: Data‐driven methods for marker and training population design by Paul Adunola, Luis Felipe V. Ferrão, Juliana Benevenuto, Camila F. Azevedo, Patricio R. Munoz

“…Our contribution in this study is threefold: (i) for the genotyping resource allocation, the use of genetic data‐driven methods to select an optimal set of markers slightly improved prediction results for all the traits; (ii) for the long‐term implication, we carried out a simulation study and emphasized that data‐driven method results in a slight improvement in genetic gain over 30 cycles than random marker sampling; and (iii) for the phenotyping resource allocation, we compared different optimization algorithms to select training population, showing that it can be leveraged to increase predictive performances. …”
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Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

“…In this direction, Proposed Optimization Algorithm V5 and Proposed Regularization Method V5 approaches have been integrated into the MobileNetv2 transfer learning model. …”
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Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…Although there is a reduction in solution optimality since the metamodel is an approximation of the original model, the metamodel methods greatly improve the computational efficiency (the computational time is reduced by 4.84 to 13.47 times in the cases of different initial points). …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…There is an urgent need for a more advanced integrated territorial space layout method. For additional spatial layout design, the study suggests a multi-objective genetic algorithm based on spatial data prediction and coupled with land simulation modeling in the context of big data and machine learning development. …”
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Adaptive Optimization and Dynamic Representation Method for Asynchronous Data Based on Regional Correlation Degree by Sichao Tang, Yuchen Zhao, Hengyi Lv, Ming Sun, Yang Feng, Zeshu Zhang

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Benchmarking and optimization of methods for the detection of identity-by-descent in high-recombining Plasmodium falciparum genomes by Bing Guo, Shannon Takala-Harrison, Timothy D O'Connor

“…Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.…”
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Comparison and Optimization of Sr Isotope Analysis in Carbonate Rocks by Multiple-step Leaching Method by Xu PAN, Ziwei SUN, Jiwei GAO, Hongmei GONG, Xiaohong WANG, Meng DUAN, Yuanyuan XIAO

“…The same concentration of acetic acid is chosen by the method of Li, et al[29], and the dissolution rate of samples with different purity began to slow down at A9, leaving about 30% of the carbonate fraction not leached. …”
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Optimal root pruning to promote growth and water use efficiency of rice seedlings by ZHU Mei, HU Chenfan, LIU Shuoshuo, LIN Shimiao, LIU Jingzhe

“…Using the membership function method, seven variables were used to comprehensively assess the impact of different pruning treatments.…”
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Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem Cells by Qimin Hai, Peter Bazeley, Juying Han, Gregory Brubaker, Jennifer Powers, Claudia M. Diaz-Montero, Jonathan D. Smith

“…<b>Methods</b>: We refined the traditional embryoid body-based differentiation strategy to create a novel three-phase method that optimizes yield, consistent quality, and reproducibility. …”
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Evaluation of optimal waste management in the plating industry based on the Delphi Method and Fuzzy Analytic Hierarchy Process (Case Study: Paitakht Industrial District of Tehran) by Mina Moeeni, Ghasemali Omrani, Nematollah Khorasani, Reza Arjmandi

“…Due to the growing production of industrial waste in spite of actions related to these wastes’ management, no comprehensive pattern was introduced at different levels. This research uses equipment and standards, including techniques such as Multi-Criteria Decision Supporting System and Fuzzy Analytic Hierarchy Process, to rank and prioritize the participation contribution of the factors that are effective in optimizing the management of waste from the plating industry in a case study, implementing the model on Paitakht Industrial District of Tehran. …”
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