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New advances in three-way decision, granular computing and concept lattice

Xizhao Wang, Jinhai Li
2020 International Journal of Machine Learning and Cybernetics  
their relationship, and discuss the problem of selecting an optimal scale combination from a generalized multi-scale decision table.  ...  In the second paper entitled "A comparison study of optimal scale combination selection in generalized multi-scale decision tables", Wei-Zhi Wu and Yee Leung put forward different scale combinations, clarify  ...  their relationship, and discuss the problem of selecting an optimal scale combination from a generalized multi-scale decision table.  ... 
doi:10.1007/s13042-020-01117-3 fatcat:rsophae27nhf5d3f6cyvnciyd4

Incremental Knowledge Acquisition for WSD: A Rough Set and IL based Method

Xu Huang, Xiulan Hao, Qing Shen, Bin Shao
2015 EAI Endorsed Transactions on Scalable Information Systems  
Experiments show the scale of decision table can be reduced dramatically by this method without performance decline.  ...  First, context of a multi-sense verb is extracted into a table; its sense is annotated by a skilled human and stored in the same table.  ...  Module of original decision table generation The generation of original table is shown in Figure 1 . 1. For each multi-sense verb do the step ii-iv; 2.  ... 
doi:10.4108/sis.2.5.e3 fatcat:73qnoasqdbfolmfhp24q43fbga

Multi-parts and multi-feature fusion in face verification

Yan Xiang, Guangda Su
2008 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
In this paper, an intra-modal fusion, that is, multi-parts and multi-feature fusion (MPMFF) for face verification is studied.  ...  Then at decision level, five matching results based on the combined-features of different parts are calculated into a final similar score according to the weighted sum rule.  ...  Acknowledgments Portions of the research in this paper use the Color FERET database of facial images collected under the FERET program.  ... 
doi:10.1109/cvprw.2008.4563107 dblp:conf/cvpr/XiangS08 fatcat:2wotqmvxnrfy5nfq4xvwucnvqe

Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction [chapter]

Hongbo Liu, Ajith Abraham, Benxian Yue
2010 Studies in Computational Intelligence  
The nature inspired population-based reduction approaches are attractive to find multiple reducts in the decision systems, which could be applied to generate multi-knowledge and to improve decision accuracy  ...  A Multi-Swarm Synergetic Optimization (MSSO) algorithm is presented for rough set reduction and multi-knowledge extraction. In the MSSO approach, different individuals encodes different reducts.  ...  For the small scale rough set reduction problem, GA has a same result than PSO. GA only provides one reduct, while PSOs provide one more reduct.  ... 
doi:10.1007/978-3-642-05179-1_21 fatcat:kylckg6pwvacbo4zhfx7ugkgcy

A Variable Precision Rough Set Model for Knowledge-assisted Management in Distance Education

Wei Zhang
2018 International Journal of Emerging Technologies in Learning (iJET)  
First, based on the theory of complete reduction and knowledge extraction, the proposed pedigree ambiguity tree was used as a strategy for obtaining complete reduction.  ...  An algorithm for obtaining a complete set of reductions was given. Then, by studying the process of knowledge extraction, a multi-knowledge extraction framework was put forward.  ...  A complete attribute reduction based on pedigree binary tree structure is proposed. A decision table is T = (U, C, D, V, f). It is converted into a β decision table Tβ=(U, C, D, Vβ, f).  ... 
doi:10.3991/ijet.v13i11.9602 fatcat:wplur2inbbflxb4gxatdqo3acy

The effect of sub-sampling in scale space texture classification using combined classifiers

M. J. Gangeh, B. M. ter Haar Romeny, C. Eswaran
2007 2007 International Conference on Intelligent and Advanced Systems  
The main issue in multiresolution techniques is the large feature space generated (multi-scale, multi-resolution, multi-derivative order).  ...  In this approach, instead of concatenating features generated from each scale/derivative, the decisions made by the base classifiers are combined in a two-stage combined classifier.  ...  The main issue in multiresolution techniques is the large feature space generated (multi-scale, multi-resolution, multi-derivative order).  ... 
doi:10.1109/icias.2007.4658498 fatcat:luzcir6tzfa6biv3tah4i77p3a

Visualization of Pareto Front Points when Solving Multi-objective Optimization Problems

Olga Kurasova, Tomas Petkus, Ernestas Filatovas
2013 Information Technology and Control  
The visualization strategy proposed is based on a combination of clustering and dimensionality reduction.  ...  In the experimental investigation of the paper, neural gas is used for data clustering, and multidimensional scaling is applied to dimensionality reduction, as well as to visualizing multidimensional data  ...  Acknowledgments One of the authors (Ernestas Filatovas) is supported by the postdoctoral fellowship is being funded by European Union Structural Funds project "Postdoctoral Fellowship Implementation in  ... 
doi:10.5755/j01.itc.42.4.3209 fatcat:qnifpnhcmnbo7hz6guc6qe32jq

The group decision-making rules based on rough sets on large scale engineering emergency

XiongWei, Su Qiuyan, Li Jinlong
2012 Systems Engineering Procedia  
large scale engineering emergency, through the establishment of a decision index system of distribution site of medical supplies in large scale engineering emergency, we obtain a reduction of decision  ...  The results show that the applying of group decision-making model based on rough set to the group decision-making of large scale engineering emergency can greatly improve the decision efficiency, and provide  ...  Acknowledgements This paper obtains subsidization of Natural Science Foundation of China.The topic name is "the research on irregular incident about group decision-making method and theory" .  ... 
doi:10.1016/j.sepro.2011.11.083 fatcat:blu74r4mzjb5favvne5bjwrad4

An efficient rough feature selection algorithm with a multi-granulation view

Jiye Liang, Feng Wang, Chuangyin Dang, Yuhua Qian
2012 International Journal of Approximate Reasoning  
Because of that the total time spent on computing reducts for sub-tables is much less than that for the original large-scale one, the algorithm yields in a much less amount of time a feature subset (the  ...  To overcome this limitation, we propose in this paper an efficient rough feature selection algorithm for large-scale data sets, which is stimulated from multi-granulation.  ...  Then, based on a reduct, a set of decision rules can be generated from a decision table. We briefly recall the notions of decision rules, which will be used in the following development.  ... 
doi:10.1016/j.ijar.2012.02.004 fatcat:yejmi62debesdpx6fydvjgbxrm

A Multi-Objective Chance-Constrained Programming Approach for Uncertainty-Based Optimal Nutrients Load Reduction at the Watershed Scale

Xujun Liu, Mengjiao Zhang, Han Su, Feifei Dong, Yao Ji, Yong Liu
2017 Water  
load reduction, which was firstly applied to nutrient load reduction in the Lake Qilu watershed of the Yunnan Plateau, China.  ...  The application of the multi-objective chance-constrained programming to optimize the reduction of watershed nutrient loads in Lake Qilu indicated that it is also applicable to other environmental problems  ...  Table 5 . 5 Scale of measures for optimal schemes 12 to 19.  ... 
doi:10.3390/w9050322 fatcat:zqjvm6fsmbaq5kppimiqo5qitu

A comparative study of many-objective optimizers on large-scale many-objective software clustering problems

Amarjeet Prajapati
2021 Complex & Intelligent Systems  
Even after vast development in the direction of L-MuOOs and L-MaOOs, the supremacy of these optimizers has not been tested on real-world optimization problems containing a large number of decision variables  ...  To address the challenges caused by such special case of MOPs, some large-scale multi-objective optimization optimizers (L-MuOOs) and large-scale many-objective optimization optimizers (L-MaOOs) have been  ...  The work [74] exploited an adaptive offspring generation in the designing of genetic algorithm based large-scale multi-objective optimization approach.  ... 
doi:10.1007/s40747-021-00270-8 fatcat:4idnkgbnpbbmvd73fhadbr5kyi

Reduct ECOC Framework for Network Intrusion Detection System

2020 International Journal of Engineering and Advanced Technology  
To tackle multi class imbalance classification problem in networks, a reduct based ECOC ensemble framework for NIDS is proposed to efficiently identify attacks in a multi class scenario.  ...  The experimental results on eight highly imbalanced datasets show that Reduct-ECOC classifier performs better than many other state-of-art multi-class classification ECOC learning methods.  ...  The proposed framework learns on different reduct subspaces and generates multiple independent dichotomy classifiers.  ... 
doi:10.35940/ijeat.b4238.029320 fatcat:kflkan7gwrevxckkvnfjy5tpqa

Palmprint Recognition Based on Curvelet Transform Decision Fusion

Wang Xinchun, Yue Kaihua, Liu Yuming, Ye Qing
2011 Procedia Engineering  
This paper utilizes the curvelet transform to extract the feature information of palmprint images on different scales, deals with the information by dimension reduction of PCA(Principal Component Analysis  ...  Curvelet transform is a multi-scale method that can represent curves most sparsely. The main feature of palmprint images is that it is made up of several main curves.  ...  It analyzes characteristics of image information on each scale, modeling after the way the human eye physiological decision, applies radial basis function to training or decision and finally chooses decision  ... 
doi:10.1016/j.proeng.2011.11.2506 fatcat:vu2gjwogtbcmhftmjvpy2cwe6i

Multi-criteria Decision Analysis: A Strategic Planning Tool for Water Loss Management

Harrison E. Mutikanga, Saroj K. Sharma, Kalanithy Vairavamoorthy
2011 Water resources management  
In this paper, an integrated multi-criteria decision-aiding framework for strategic planning of water loss management is presented.  ...  The PROMETHEE II method was applied within the framework in prioritizing water loss reduction options for Kampala city.  ...  The authors are grateful to all the NWSC staff and the GTZ technical adviser to NWSC who participated in the questionnaire survey and brainstorming sessions.  ... 
doi:10.1007/s11269-011-9896-9 fatcat:riobaxcgrbct3km4iqa2cprssi

Approaches to Multi-Objective Optimization and Assessment of Green Infrastructure and Their Multi-Functional Effectiveness: A Review

Jia Wang, Jiahong Liu, Hao Wang, Chao Mei
2020 Water  
Then, the main components of GI multi-objective optimization including the spatial scale application, optimization objectives, decision variables, optimization methods and optimization procedure as well  ...  There is no consensus on how to measure and optimize the integrated multi-functional effectiveness of GI.  ...  Future research should focus on the following: (1) improving the integrated multifunctionality of GI by strengthening multidisciplinary research and interdisciplinary cooperation; (2) enhancing the integration  ... 
doi:10.3390/w12102714 fatcat:yrn2chg2xfcz5glh7i66c6opde
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