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Antagonistic-information-dependent integral-type event-trigger scheme for bipartite synchronization of cooperative-competitive neural networks and its application 用于合作竞争神经网络两端同步的拮抗-信息依赖积分型事件触发方案及其应用

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121617

Xindong Si , Yingjie Fan , Zhen Wang

{"title":"Antagonistic-information-dependent integral-type event-trigger scheme for bipartite synchronization of cooperative-competitive neural networks and its application","authors":"Xindong Si , Yingjie Fan , Zhen Wang","doi":"10.1016/j.ins.2024.121617","DOIUrl":"10.1016/j.ins.2024.121617","url":null,"abstract":"<div><div>This paper focuses on the bipartite synchronization problem for cooperative-competitive neural networks (CCNNs) by using an antagonistic-information-dependent integral-type event-trigger scheme. Here, the designed antagonistic-information implies that both the cooperation and competition interactions of CCNNs are utilized to design trigger scheme. First, the signed digraph theory, in the presence of structurally balanced topology, is used to describe the antagonistic interactions among neuron nodes. On this basis, such a trigger scheme consisting of antagonistic-information and integral term is proposed to relax communication burden, which can remember the evolution information of CCNNs dynamic process. Meanwhile, the discontinuity of event-triggered scheme can avoid the occurrence of Zeno behavior directly without complicated mathematical analysis. Then, an important lemma is derived to facilitate bipartite synchronization problem. By constructing appropriate Lyapunov function, two novel bipartite synchronization criteria are developed by utilizing the hybrid Lyapunov theories, new lemma, and inequality techniques. At last, an application and an effective example are presented to illustrate the validity and advantage of the proposed method.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121617"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A context-enhanced neural network model for biomedical event trigger detection 用于生物医学事件触发检测的语境增强型神经网络模型

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121625

Zilin Wang , Yafeng Ren , Qiong Peng , Donghong Ji

{"title":"A context-enhanced neural network model for biomedical event trigger detection","authors":"Zilin Wang , Yafeng Ren , Qiong Peng , Donghong Ji","doi":"10.1016/j.ins.2024.121625","DOIUrl":"10.1016/j.ins.2024.121625","url":null,"abstract":"<div><div>As an important component of biomedical event extraction, biomedical event trigger detection has received extensive research attention in recent years. Most studies focus on designing various models or features according to the original text itself, but fail to leverage contextual information of the original text from external knowledge base such as Wikipedia, which is publicly available. To address the issue, we propose a context-enhanced neural network model that automatically integrates the related information from external knowledge base for biomedical event trigger detection. Specifically, the proposed model first extracts the related context of the original text from external knowledge base. Then the original text and its context are sequentially fed into the BERT embedding layer and Transformer convolution layer to learn high-level semantic representation. Finally, the probability of possible tags is calculated using the CRF layer. Experimental results on the MLEE dataset show our proposed model achieves 86.83% F1 score, outperforming the existing methods and context-enhanced baseline systems significantly. Experimental analysis also indicates the effectiveness of contextual information for trigger detection in biomedical domain.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121625"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of a class of singular Boolean control networks 一类奇异布尔控制网络的识别

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121627

Rong Zhao , Jun-e Feng , Qingchun Meng , Biao Wang

{"title":"Identification of a class of singular Boolean control networks","authors":"Rong Zhao , Jun-e Feng , Qingchun Meng , Biao Wang","doi":"10.1016/j.ins.2024.121627","DOIUrl":"10.1016/j.ins.2024.121627","url":null,"abstract":"<div><div>System identification, recognized as an inverse control problem, is a significant aspect of modern control theory. This study focuses on addressing the identification problem related to a specific category of singular Boolean networks (SBNs) and singular Boolean control networks (SBCNs). The introduction of two novel concepts, namely the admissibility and solvability matrices, enables the establishment of conditions for determining the existence and uniqueness of solutions for SBNs and SBCNs. Then criteria are deduced to identify the number of dynamic equations. Based on observability, controllability and detectability, several conditions are presented to characterize identification. Among them, two crucial results show: When the solution to an SBN or SBCN is unique, the SBN is identifiable if and only if it is observable, and the SBCN is identifiable if and only if it is O1-observable, which is the most general type of observability. Besides, effective algorithms are devised to implement identification. Furthermore, the study delves into the normalization issue using the admissibility matrix, which provides a possibility to reduce the identified SBN or SBCN to a lower-order BN or BCN.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121627"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic evidence fusion neural networks with uncertainty theory and its application in brain network analysis 具有不确定性理论的动态证据融合神经网络及其在脑网络分析中的应用

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121622

Weiping Ding , Tao Hou , Jiashuang Huang , Hengrong Ju , Shu Jiang

{"title":"Dynamic evidence fusion neural networks with uncertainty theory and its application in brain network analysis","authors":"Weiping Ding , Tao Hou , Jiashuang Huang , Hengrong Ju , Shu Jiang","doi":"10.1016/j.ins.2024.121622","DOIUrl":"10.1016/j.ins.2024.121622","url":null,"abstract":"<div><div>Deep learning has demonstrated significant potential and advantages, achieving notable success in the medical field, particularly in the application of brain network analysis. However, most models ignore the uncertainty caused by inconsistent view quality and fail to effectively leverage the potential correlations and temporal sequences present in multi-view data, preventing neural networks from fully showcasing their strengths. To this end, this paper proposes dynamic evidence fusion neural networks (DEF-NNs) with uncertainty theory, and applies it to brain network analysis. Our model is established within a multi-view learning framework that considers the functional connections under each window as a view. We employ a dynamic evidence learning module to capture the evidence for each time window of the dynamic brain network, utilizing three distinct convolutional filters to extract feature maps. Then, a dynamic evidence fusion mechanism is designed and a dynamic trust function is constructed according to the temporal nature of dFC data. The evidence generated by multiple windows is fused at the decision level of classification, dealing with the uncertainty caused by inconsistent view quality and improving the classification performance. We verified the effectiveness of DEF-NNs through comparison with advanced algorithms on three schizophrenia datasets, and the results show that DEF-NNs significantly improved the classification performance of brain disease diagnosis tasks.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121622"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-dimensional expensive optimization by Kriging-assisted multiobjective evolutionary algorithm with dimensionality reduction 利用克里金辅助多目标进化算法进行高维昂贵优化并降低维度

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121620

Zeyuan Yan , Yuren Zhou , Xiaoyu He , Chupeng Su , Weigang Wu

{"title":"High-dimensional expensive optimization by Kriging-assisted multiobjective evolutionary algorithm with dimensionality reduction","authors":"Zeyuan Yan , Yuren Zhou , Xiaoyu He , Chupeng Su , Weigang Wu","doi":"10.1016/j.ins.2024.121620","DOIUrl":"10.1016/j.ins.2024.121620","url":null,"abstract":"<div><div>Surrogate-assisted multi-objective evolutionary algorithms (SA-MOEAs) have made significant progress in solving expensive multi- and many-objective optimization problems. However, most of them perform well in low-dimensional settings but often struggle with high-dimensional problems. The main reason is that some techniques used in SA-MOEAs, like the Kriging model, are ineffective in exploring high-dimensional search spaces. As a result, this research investigates frameworks incorporating dimensionality reduction techniques to conduct modeling and optimization tasks on dimensionality reduction decision spaces. This article uses a singular value decomposition method to map the high-dimensional decision space into a low-dimensional one, then employs a feature fusion strategy to combine low-dimensional features with high-dimensional ones for better representation. Subsequently, these low-dimensional features are used to train the Kriging-based surrogates to select promising solutions within a limited number of function evaluations. In addition, this article provides two types of evolutionary modes to balance exploration and exploitation. Experimental results demonstrate the effectiveness of the proposed SA-MOEA compared to several state-of-the-art algorithms.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121620"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Configuration of liveness-enforcing initial marking with the minimum resources for resource allocation systems 为资源分配系统配置最少资源的增强活泼性初始标记

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121623

Yanxiang Feng , Sida Ren , Keyi Xing , Yikang Yang , MengChu Zhou

{"title":"Configuration of liveness-enforcing initial marking with the minimum resources for resource allocation systems","authors":"Yanxiang Feng , Sida Ren , Keyi Xing , Yikang Yang , MengChu Zhou","doi":"10.1016/j.ins.2024.121623","DOIUrl":"10.1016/j.ins.2024.121623","url":null,"abstract":"<div><div>The enforcement of liveness is crucial for Petri nets models of resource allocation systems (RASs). It is interesting yet very challenging to establish an initial marking for Petri net plants so that the net is live. Such an initial marking is referred to as <em>liveness-enforcing initial marking</em> (LIM). Despite existing literature presenting various LIMs, no studies have addressed the issue of minimizing the number of resources in an LIM. This work focuses on designing an LIM with the minimum resources (LIM-MR) for a class of Petri nets called <em>systems of sequential systems with shared resources</em> (S<sup>4</sup>PRs) by assigning a token capacity to each resource place, such that the sum of all involved resources is minimized. This work first establishes a kind of necessary and sufficient liveness condition for S<sup>4</sup>PR, which is then encoded into a series of variables and constraints in a mixed-integer programming (MIP) formulation. Although LIM-MR may not be unique, solving the proposed MIP formulation can obtain at least one LIM-MR for S<sup>4</sup>PR under consideration. The experimental results show the solvability of this approach for S<sup>4</sup>PRs.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121623"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linear fuzzy partial differential equations for A-linearly correlated fuzzy processes A 线性相关模糊过程的线性模糊偏微分方程

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121629

M. Shahidi, L.C. Barros, E. Esmi

引用次数: 0

Event-based adaptive neural resilient formation control for MIMO nonlinear MASs under actuator saturation and denial-of-service attacks 执行器饱和与拒绝服务攻击下的多输入多输出非线性 MAS 的基于事件的自适应神经弹性编队控制

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121619

Xiangjun Wu , Ning Xu , Shuo Ding , Xudong Zhao , Ben Niu , Wencheng Wang

{"title":"Event-based adaptive neural resilient formation control for MIMO nonlinear MASs under actuator saturation and denial-of-service attacks","authors":"Xiangjun Wu , Ning Xu , Shuo Ding , Xudong Zhao , Ben Niu , Wencheng Wang","doi":"10.1016/j.ins.2024.121619","DOIUrl":"10.1016/j.ins.2024.121619","url":null,"abstract":"<div><div>This paper focuses on the distributed event-triggered adaptive neural resilient time-varying formation control problem for a class of multiple-input multiple-output nonlinear multi-agent systems, where all network communication links between agents are subjected to denial-of-service (DoS) attacks simultaneously. A second-order resilient time-varying formation estimator is designed to obtain the unknown leader information in DoS attack active intervals. Meanwhile, a state-triggering mechanism (STM) is designed to save system communication resources. Nevertheless, the STM can lead to virtual control laws being non-differentiable. To circumvent the problem, we first design an adaptive neural resilient formation control scheme. Then, based on the adaptive neural resilient formation control scheme, we replace continuous states with intermittent ones. By utilizing a dynamic filtering technique, an event-based adaptive neural resilient formation control scheme is designed. The key technology of control scheme design is to establish an improved first-order auxiliary system to deal with the negative impact of actuator saturation. It is proved that formation tracking errors can converge to a residual set around zero, and all signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results are presented to show the effectiveness of the control scheme.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121619"},"PeriodicalIF":8.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Associative operations on the poset of closed intervals of a given lower-bounded poset 给定下界正集的闭区间正集的关联运算

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-08 DOI: 10.1016/j.ins.2024.121630

Yexing Dan, Xiaodong Pan

引用次数: 0

Regret-based domination three-way decision-making model with circular spherical fuzzy Mahalanobis distance 基于遗憾的支配三方决策模型与环形球面模糊 Mahalanobis 距离

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2024-11-07 DOI: 10.1016/j.ins.2024.121616

Shahzaib Ashraf , Chiranjibe Jana , Wania Iqbal , Muhammet Deveci

{"title":"Regret-based domination three-way decision-making model with circular spherical fuzzy Mahalanobis distance","authors":"Shahzaib Ashraf , Chiranjibe Jana , Wania Iqbal , Muhammet Deveci","doi":"10.1016/j.ins.2024.121616","DOIUrl":"10.1016/j.ins.2024.121616","url":null,"abstract":"<div><div>This article proposes a revolutionary three-way multi-attribute model in response to the increased complexity and risk in decision-making processes. This model combines three-way decision rules with the influential behavioral theories of regret and prospect. To address uncertainties in evaluation data, a circular spherical fuzzy set is seamlessly integrated into the information system, noting that this method can also be smoothly applied to disc spherical fuzzy sets (D-SFSs). Moreover, a pioneering method utilizing correlation coefficients and variances is introduced for attribute weighting. The conventional Mahalanobis distance is extended to a circular, spherical, fuzzy Mahalanobis distance. A novel approach is developed to estimate conditional probabilities based on the distinct regret-based dominating and rejoice-based dominating relations in circular spherical fuzzy sets (C-SFSs). Additionally, three scoring systems based on prospect theory yield despondent, expectant, and balanced decision-making strategies and provide priceless insights into various decision-maker mindsets. Furthermore, to illustrate the practical application of these methods with D-SFSs information, an example has been solved utilizing D-SFSs.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"691 ","pages":"Article 121616"},"PeriodicalIF":8.1,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0