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

Some identities of degenerate multi-poly-Changhee polynomials and numbers 退化多重多项式-长熙多项式与数的一些恒等式

4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023367

Sang Jo Yun, Sangbeom Park, Jin-Woo Park, Jongkyum Kwon

引用次数: 0

F-LSTM: Federated learning-based LSTM framework for cryptocurrency price prediction F-LSTM:用于加密货币价格预测的基于联邦学习的LSTM框架

4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023330

Nihar Patel, Nakul Vasani, Nilesh Kumar Jadav, Rajesh Gupta, Sudeep Tanwar, Zdzislaw Polkowski, Fayez Alqahtani, Amr Gafar

{"title":"F-LSTM: Federated learning-based LSTM framework for cryptocurrency price prediction","authors":"Nihar Patel, Nakul Vasani, Nilesh Kumar Jadav, Rajesh Gupta, Sudeep Tanwar, Zdzislaw Polkowski, Fayez Alqahtani, Amr Gafar","doi":"10.3934/era.2023330","DOIUrl":"https://doi.org/10.3934/era.2023330","url":null,"abstract":"<abstract>In this paper, a distributed machine-learning strategy, i.e., federated learning (FL), is used to enable the artificial intelligence (AI) model to be trained on dispersed data sources. The paper is specifically meant to forecast cryptocurrency prices, where a long short-term memory (LSTM)-based FL network is used. The proposed framework, i.e., <italic>F-LSTM</italic> utilizes FL, due to which different devices are trained on distributed databases that protect the user privacy. Sensitive data is protected by staying private and secure by sharing only model parameters (weights) with the central server. To assess the effectiveness of <italic>F-LSTM</italic>, we ran different empirical simulations. Our findings demonstrate that <italic>F-LSTM</italic> outperforms conventional approaches and machine learning techniques by achieving a loss minimal of $ 2.3 times 10^{-4} $. Furthermore, the <italic>F-LSTM</italic> uses substantially less memory and roughly half the CPU compared to a solely centralized approach. In comparison to a centralized model, the <italic>F-LSTM</italic> requires significantly less time for training and computing. The use of both FL and LSTM networks is responsible for the higher performance of our suggested model (<italic>F-LSTM</italic>). In terms of data privacy and accuracy, <italic>F-LSTM</italic> addresses the shortcomings of conventional approaches and machine learning models, and it has the potential to transform the field of cryptocurrency price prediction.</abstract>","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136257154","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

Decision making in railway interlocking systems based on calculating the remainder of dividing a polynomial by a set of polynomials 基于多项式除以多项式集余数计算的铁路联锁系统决策

4区数学

Electronic Research Archive Pub Date : 2023-01-01 DOI: 10.3934/era.2023313

Antonio Hernando, Eugenio Roanes-Lozano, José Luis Galán-García, Gabriel Aguilera-Venegas

{"title":"Decision making in railway interlocking systems based on calculating the remainder of dividing a polynomial by a set of polynomials","authors":"Antonio Hernando, Eugenio Roanes-Lozano, José Luis Galán-García, Gabriel Aguilera-Venegas","doi":"10.3934/era.2023313","DOIUrl":"https://doi.org/10.3934/era.2023313","url":null,"abstract":"<abstract>Decision-making in a railway station regarding the compatibility of the positions of the switches of the turnouts and the indications (proceed/stop) of the railway colour light signals is a safety-critical issue that is considered very labor-intensive. Different authors have proposed alternative solutions to automate its supervision, which is performed by the so-called railway interlocking systems. The classic railway interlocking systems are route-based and their compatibility is predetermined (usually by human experts): only some chosen routes are simultaneously allowed. Some modern railway interlocking systems are geographical and make decisions on the fly, but are unsuitable if the station is very large and the number of trains is high. In this paper, we present a completely new algebraic model for decision-making in railway interlocking systems, based on other computer algebra techniques, that bypasses the disadvantages of the approaches mentioned above (its performance does not depend on the number of trains in the railway station and can be used in large railway stations). The main goal of this work is to provide a mathematical solution to the interlocking problems. We prove that our approach solves it in linear time. Although our approach is interesting from a theoretical perspective, it has a significant limitation: it can hardly be adopted in an actual interlocking implementation, mainly due to the heavy certification requirements for this kind of safety-critical application. Nevertheless, the results may be useful for simulations that do not require certification credit.</abstract>","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135498114","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

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":"33 1","pages":""},"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