Electronic Research Archive最新文献

On $ p $-Laplacian Kirchhoff-Schrödinger-Poisson type systems with critical growth on the Heisenberg group 关于Heisenberg群上具有临界增长的$p$-Laplaccian-Kirchhoff-Schrödinger-Poisson型系统

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-08-19 DOI: 10.3934/era.2023292

Shujie Bai, Yueqiang Song, Dušan D. Repovš

引用次数: 0

Fredholm inversion around a singularity: Application to autoregressive time series in Banach space 围绕奇点的Fredholm反演:在Banach空间中自回归时间序列中的应用

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-04-08 DOI: 10.3934/era.2023252

Won-Ki Seo

引用次数: 0

Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation 海上运输不确定条件下船舶检验规划的随机优化模型

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023006

Ran Yan, Ying Yang, Yuquan Du

{"title":"Stochastic optimization model for ship inspection planning under uncertainty in maritime transportation","authors":"Ran Yan, Ying Yang, Yuquan Du","doi":"10.3934/era.2023006","DOIUrl":"https://doi.org/10.3934/era.2023006","url":null,"abstract":"Maritime transportation plays a significant role in international trade and global supply chains. Ship navigation safety is the foundation of operating maritime business smoothly. Recently, more and more attention has been paid to marine environmental protection. To enhance maritime safety and reduce pollution in the marine environment, various regulations and conventions are proposed by international organizations and local governments. One of the most efficient ways of ensuring that the related requirements are complied with by ships is ship inspection by port state control (PSC). In the procedure of ship inspection, a critical issue for the port state is how to select ships of higher risk for inspection and how to optimally allocate the limited inspection resources to these ships. In this study, we adopt prediction and optimization approaches to address the above issues. We first predict the number of ship deficiencies based on a k nearest neighbor (kNN) model. Then, we propose three optimization models which aim for a trade-off between the reward for detected deficiencies and the human resource cost of ship inspection. Specifically, we first follow the predict-then-optimize framework and develop a deterministic optimization model. We also establish two stochastic optimization models where the distribution of ship deficiency number is estimated by the predictive prescription method and the global prescriptive analysis method, respectively. Furthermore, we conduct a case study using inspection data at the Hong Kong port to compare the performances of the three optimization models, from which we conclude that the predictive prescription model is more efficient and effective for this problem.","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70243576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A priori bounds and existence of smooth solutions to a $ L_p $ Aleksandrov problem for Codazzi tensor with log-convex measure 具有对数凸测度的Codazzi张量$ L_p $ Aleksandrov问题的先验界和光滑解的存在性

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023042

Zhengmao Chen

引用次数: 0

Regress 3D human pose from 2D skeleton with kinematics knowledge 利用运动学知识从二维骨架回归三维人体姿态

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023075

Longkui Jiang, Yuru Wang, Weijia Li

引用次数: 0

An improved fixed-time stabilization problem of delayed coupled memristor-based neural networks with pinning control and indefinite derivative approach 基于固定控制和不定导数方法的延迟耦合记忆电阻神经网络的改进定时镇定问题

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023123

Chao Yang, J. Wu, Zhengyang Qiao

引用次数: 0

Existence and multiplicity of positive solutions for one-dimensional $ p $-Laplacian problem with sign-changing weight 一维变权$ p $-拉普拉斯问题正解的存在性和多重性

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023156

Liangying Miao, Man Xu, Zhiqian He

引用次数: 0

EECHS-ARO: Energy-efficient cluster head selection mechanism for livestock industry using artificial rabbits optimization and wireless sensor networks 基于人工兔子优化和无线传感器网络的畜牧业节能簇头选择机制

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023158

Rajakumar Ramalingam, S. B., Shakila Basheer, Prakash Balasubramanian, Mamoon Rashid, Gitanjali Jayaraman

{"title":"EECHS-ARO: Energy-efficient cluster head selection mechanism for livestock industry using artificial rabbits optimization and wireless sensor networks","authors":"Rajakumar Ramalingam, S. B., Shakila Basheer, Prakash Balasubramanian, Mamoon Rashid, Gitanjali Jayaraman","doi":"10.3934/era.2023158","DOIUrl":"https://doi.org/10.3934/era.2023158","url":null,"abstract":"In the livestock industry, wireless sensor networks (WSNs) play a significant role in monitoring many fauna health statuses and behaviors. Energy preservation in WSNs is considered one of the critical, complicated tasks since the sensors are coupled to constrained resources. Therefore, the clustering approach has proved its efficacy in preserving energy in WSNs. In recent studies, various clustering approaches have been introduced that use optimization techniques to improve the network lifespan by decreasing energy depletion. Yet, they take longer to converge and choose the optimal cluster heads in the network. In addition, the energy is exhausted quickly in the network. This paper introduces a novel optimization technique, i.e., an artificial rabbits optimization algorithm-based energy efficient cluster formation (EECHS-ARO) approach in a WSN, to extend the network lifetime by minimizing the energy consumption rate. The EECHS-ARO technique balances the search process in terms of enriched exploration and exploitation while selecting the optimal cluster heads. The experimentation was carried out on a MATLAB 2021a platform with varying sensor nodes. The obtained results of EECHS-ARO are contrasted with other existing approaches via teaching–learning based optimization algorithm (TLBO), ant lion optimizer (ALO) and quasi oppositional butterfly optimization algorithm (QOBOA). The proposed EECHS-ARO enriches the network lifespan by ~15% and improves the packet delivery ratio by ~5%.","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70245319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Barycentric rational interpolation method for solving KPP equation 求解KPP方程的质心有理插值法

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023152

Jin Li, Yongling Cheng

引用次数: 3

A data-driven on-site injury severity assessment model for car-to-electric-bicycle collisions based on positional relationship and random forest 基于位置关系和随机森林的汽车与电动自行车碰撞现场伤害严重程度评估模型

IF 0.8 4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023173

Ye Yu, Zhiyuan Liu

{"title":"A data-driven on-site injury severity assessment model for car-to-electric-bicycle collisions based on positional relationship and random forest","authors":"Ye Yu, Zhiyuan Liu","doi":"10.3934/era.2023173","DOIUrl":"https://doi.org/10.3934/era.2023173","url":null,"abstract":"Vulnerable road users (VRUs) are usually more susceptible to fatal injuries. Accurate and rapid assessment of VRU injury severity at the accident scene can provide timely support for decision-making in emergency response. However, evaluating VRU injury severity at the accident scene usually requires medical knowledge and medical devices. Few studies have explored the possibility of using on-site positional relationship to assess injury severity, which could provide a new perspective for on-site transportation professionals to assess accident severity. This study proposes a data-driven on-site injury severity assessment model for car-to-electric-bicycle accidents based on the relationship between the final resting positions of the car, electric bicycle and cyclist at the accident scene. Random forest is employed to learn the accident features from the at-scene positional relationship among accident participants, by which injury severity of the cyclist is assessed. Conditional permutation importance, which can account for correlation among predictor variables, is adopted to reflect the importance of predictor variables more accurately. The proposed model is demonstrated using simulated car-to-electric-bicycle collision data. The results show that the proposed model has good performance in terms of overall accuracy and is balanced in recognizing both fatal and non-fatal accidents. Model performance under partial information confirms that the position information of the electric bicycle is more important than the position information of the cyclist in assessing injury severity.","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70245719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0