Inf. Sci.最新文献_第10页

Tensor subspace clustering using consensus tensor low-rank representation 用一致张量低秩表示的张量子空间聚类

Inf. Sci. Pub Date : 2022-07-01 DOI: 10.1016/j.ins.2022.07.049

Bing Cai, Gui-Fu Lu

引用次数: 11

Unsupervised manifold learning with polynomial mapping on symmetric positive definite matrices 对称正定矩阵上多项式映射的无监督流形学习

Inf. Sci. Pub Date : 2022-07-01 DOI: 10.1016/j.ins.2022.07.077

Hao Xu

引用次数: 3

A hybrid level-based learning swarm algorithm with mutation operator for solving large-scale cardinality-constrained portfolio optimization problems 基于变异算子的混合层次学习群算法求解大规模基数约束投资组合优化问题

Inf. Sci. Pub Date : 2022-06-29 DOI: 10.48550/arXiv.2206.14760

M. Kaucic, Filippo Piccotto, Gabriele Sbaiz, G. Valentinuz

{"title":"A hybrid level-based learning swarm algorithm with mutation operator for solving large-scale cardinality-constrained portfolio optimization problems","authors":"M. Kaucic, Filippo Piccotto, Gabriele Sbaiz, G. Valentinuz","doi":"10.48550/arXiv.2206.14760","DOIUrl":"https://doi.org/10.48550/arXiv.2206.14760","url":null,"abstract":"In this work, we propose a hybrid variant of the level-based learning swarm optimizer (LLSO) for solving large-scale portfolio optimization problems. Our goal is to maximize a modified formulation of the Sharpe ratio subject to cardinality, box and budget constraints. The algorithm involves a projection operator to deal with these three constraints simultaneously and we implicitly control transaction costs thanks to a rebalancing constraint. We also introduce a suitable exact penalty function to manage the turnover constraint. In addition, we develop an ad hoc mutation operator to modify candidate exemplars in the highest level of the swarm. The experimental results, using three large-scale data sets, show that the inclusion of this procedure improves the accuracy of the solutions. Then, a comparison with other variants of the LLSO algorithm and two state-of-the-art swarm optimizers points out the outstanding performance of the proposed solver in terms of exploration capabilities and solution quality. Finally, we assess the profitability of the portfolio allocation strategy in the last five years using an investible pool of 1119 constituents from the MSCI World Index.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"51 1","pages":"321-339"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86559596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Toward multi-target self-organizing pursuit in a partially observable Markov game 部分可观察马尔可夫对策中多目标自组织追击的研究

Inf. Sci. Pub Date : 2022-06-24 DOI: 10.48550/arXiv.2206.12330

Lijun Sun, Yu-Cheng Chang, Chao Lyu, Ye Shi, Yuhui Shi, Chin-Teng Lin

{"title":"Toward multi-target self-organizing pursuit in a partially observable Markov game","authors":"Lijun Sun, Yu-Cheng Chang, Chao Lyu, Ye Shi, Yuhui Shi, Chin-Teng Lin","doi":"10.48550/arXiv.2206.12330","DOIUrl":"https://doi.org/10.48550/arXiv.2206.12330","url":null,"abstract":"The multiple-target self-organizing pursuit (SOP) problem has wide applications and has been considered a challenging self-organization game for distributed systems, in which intelligent agents cooperatively pursue multiple dynamic targets with partial observations. This work proposes a framework for decentralized multi-agent systems to improve the implicit coordination capabilities in search and pursuit. We model a self-organizing system as a partially observable Markov game (POMG) featured by large-scale, decentralization, partial observation, and noncommunication. The proposed distributed algorithm: fuzzy self-organizing cooperative coevolution (FSC2) is then leveraged to resolve the three challenges in multi-target SOP: distributed self-organizing search (SOS), distributed task allocation, and distributed single-target pursuit. FSC2 includes a coordinated multi-agent deep reinforcement learning (MARL) method that enables homogeneous agents to learn natural SOS patterns. Additionally, we propose a fuzzy-based distributed task allocation method, which locally decomposes multi-target SOP into several single-target pursuit problems. The cooperative coevolution principle is employed to coordinate distributed pursuers for each single-target pursuit problem. Therefore, the uncertainties of inherent partial observation and distributed decision-making in the POMG can be alleviated. The experimental results demonstrate that by decomposing the SOP task, FSC2 achieves superior performance compared with other implicit coordination policies fully trained by general MARL algorithms. The scalability of FSC2 is proved that up to 2048 FSC2 agents perform efficient multi-target SOP with almost 100 percent capture rates. Empirical analyses and ablation studies verify the interpretability, rationality, and effectiveness of component algorithms in FSC2.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"17 1","pages":"119475"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89016589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Analysis of the Admissibility of the Objective Functions Applied in Evolutionary Multi-objective Clustering 进化多目标聚类中目标函数的可接受性分析

Inf. Sci. Pub Date : 2022-06-19 DOI: 10.48550/arXiv.2206.09483

Cristina Y. Morimoto, A. Pozo, M. D. Souto

引用次数: 0

Efficient reversible data hiding via two layers of double-peak embedding 通过两层双峰嵌入实现有效的可逆数据隐藏

Inf. Sci. Pub Date : 2022-06-08 DOI: 10.48550/arXiv.2206.03838

Fuhu Wu, Jian Sun, Shun Zhang, Zhili Chen

引用次数: 1

A q-rung orthopair fuzzy decision-making model with new score function and best-worst method for manufacturer selection 基于新评分函数和最佳-最差法的q阶矫形模糊决策模型

Inf. Sci. Pub Date : 2022-06-01 DOI: 10.1016/j.ins.2022.06.061

Liming Xiao, Guangquan Huang, W. Pedrycz, D. Pamučar, Luis Martínez, Genbao Zhang

引用次数: 38

A multiphase information fusion strategy for data-driven quality prediction of industrial batch processes 基于数据驱动的工业批处理质量预测的多相信息融合策略

Inf. Sci. Pub Date : 2022-06-01 DOI: 10.1016/j.ins.2022.06.057

Yanning Sun, Wei Qin, Hongwei Xu, Run Tan, Zhanhong Zhang, Wenle Shi

引用次数: 14

Semi-Parametric Contextual Bandits with Graph-Laplacian Regularization 图-拉普拉斯正则化的半参数上下文强盗

Inf. Sci. Pub Date : 2022-05-17 DOI: 10.48550/arXiv.2205.08295

Y. Choi, Gi-Soo Kim, Seung-Jin Paik, M. Paik

引用次数: 2

Some neighborhood-related fuzzy covering-based rough set models and their applications for decision making 基于邻域模糊覆盖的粗糙集模型及其决策应用

Inf. Sci. Pub Date : 2022-05-13 DOI: 10.48550/arXiv.2205.10125

Gongao Qi, Bin Yang, Wei Li

{"title":"Some neighborhood-related fuzzy covering-based rough set models and their applications for decision making","authors":"Gongao Qi, Bin Yang, Wei Li","doi":"10.48550/arXiv.2205.10125","DOIUrl":"https://doi.org/10.48550/arXiv.2205.10125","url":null,"abstract":"Fuzzy rough set (FRS) has a great effect on data mining processes and the fuzzy logical operators play a key role in the development of FRS theory. In order to further generalize the FRS theory to more complicated data environments, we firstly propose four types of fuzzy neighborhood operators based on fuzzy covering by overlap functions and their implicators in this paper. Meanwhile, the derived fuzzy coverings from an original fuzzy covering are defined and the equalities among overlap function-based fuzzy neighborhood operators based on a finite fuzzy covering are also investigated. Secondly, we prove that new operators can be divided into seventeen groups according to equivalence relations, and the partial order relations among these seventeen classes of operators are discussed, as well. Go further, the comparisons with $ t$-norm-based fuzzy neighborhood operators given by D'eer et al. are also made and two types of neighborhood-related fuzzy covering-based rough set models, which are defined via different fuzzy neighborhood operators that are on the basis of diverse kinds of fuzzy logical operators proposed. Furthermore, the groupings and partially order relations are also discussed. Finally, a novel fuzzy TOPSIS methodology is put forward to solve a biosynthetic nanomaterials select issue, and the rationality and enforceability of our new approach is verified by comparing its results with nine different methods.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"37 1","pages":"799-843"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80748013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4