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检索条件"任意字段=4th International Conference on Art, Science, and Engineering of Programming, Programming 2020"

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A Fuzzily Partitioned Interval Function Model for Ordinal Regression

A Fuzzily Partitioned Interval Function Model for Ordinal Re...

引用

international conference on Computer and Information sciences (ICCOINS)

作者： Masahiro Inuiguchi Hiroki Inoue Graduate School of Engineering Science Osaka University Toyonaka Japan

In this paper, we propose a fuzzily partitioned interval function model for ordinal regression as an extension of the interval UTA method. UTA method is known as a decision-aiding tool in multiple criteria decision problems. In UTA method, an additive utility function compatible to given preference information is identified under the assumption of the additive independence. However, this assumption is rather strong as is known in multiattribute utility theory. In this paper, we propose an interval utility model identified under a weaker assumption. We assume that the utility function is expressed by a fuzzy reasoning model with additive interval utility functions, a generalized additive utility function model. We show that the proposed model can be identified by solving a linear programming problem under given preference information and that preference evaluation can be done easily by using the identified model. We examine the performance of the proposed model by numerical experiments assuming that the decision maker has a utility function under the assumption of utility independence.

关键词： Additives Numerical models Linear programming Computational modeling Electronic mail Utility theory Fuzzy reasoning

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Brain data base (BDB) 4th

Brain data base (BDB)

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4th international conference on Database and Expert Systems Applications, DEXA 1993

作者： Anogianakis, G. Krotopoulou, A. Spirakis, P. Terpou, D. Tsakalidis, A. Faculty of Medicine University of Thessaloniki Greece Department of Computer Engineering and Informatics University of Patras Greece

ISBN: (纸本)9783540572343

the Brain Data Base (BDB) is an innovative database that keeps (in a structural way) those anatomical and functional features of the human brain, suitable for applying the principles of biomagnetism in order to localize epileptic foci. It handles complex and non-uniform 3-D objects and admits efficient query evaluation through state-of the art computational geometry techniques. the proposed logical model of the BDB may serve as a framework for other specialized databases which deal with non-standard and involved topological information. © Springer-Verlag Berlin Heidelberg 1993.

关键词： Computational geometry

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Book Recommendation System using R programming - A Comparative Study.

Book Recommendation System using R Programming - A Comparati...

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Innovative Practices in Technology and Management (ICIPTM), international conference on

作者： Sandhiya. B K. N. Meera Said Broumi Dept. of Computer Science and Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India Dept. of Mathematics Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India Laboratory of Information Processing Faculty of Science Ben M’Sik University of Hassan II Casablanca Morocco

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

A Recommendation System (also known as Recommender System) is built for the purpose of recommending similar items to the user based on their interest. the item can be anything like movies, music, books, songs, etc. Many famous platforms such as Netflix and YouTube also use recommendation system. this paper focuses on comparing and studying the performance of the Recommender System for books that uses various different techniques such as k-means Clustering, PCA, Feature Selection, etc.

关键词： Video on demand Data analysis Accuracy Clustering algorithms programming Motion pictures Feature extraction

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Predator — An experience guided configuration optimizer for Hadoop MapReduce

Predator — An experience guided configuration optimizer for...

引用

IEEE international conference on Cloud Computing Technology and science (CloudCom)

作者： Kewen Wang Xuelian Lin Wenzhong Tang School of Computer Science and Engineering Beihang University Beijing China

MapReduce is a distributed computing programming framework which provides an effective solution to the data processing challenge. As an open-source implementation of MapReduce, Hadoop has been widely used in practice. the performance of Hadoop MapReduce heavily depends on its configuration settings, so tuning these configuration parameters could be an effective way to improve its performance. However, picking out the optimal configuration settings is not easy for the time consuming nature of MapReduce together with the high dimensional and nonlinear features of its configuration optimization. In this paper, we introduce Predator, an experience guided configuration optimizer, which does not treat the optimization problem as a pure black-box problem but utilizes useful experience learnt from Hadoop MapReduce configuration practice to assist the optimizing process. the optimizer uses job execution time estimated by a practical MapReduce cost model as the objective function, and classifies Hadoop MapReduce parameters into different groups by their different tunable levels to shrink search space. Furthermore, the optimization algorithm of the optimizer uses the idea of subspace division to prevent local optimum problem, and it could also reduce the searching time by cutting down the cost in visiting unpromising points in search space. Experiments on Hadoop clusters demonstrate the effectiveness and efficiency of the optimizer.

关键词： Linear programming Optimization Search problems Tuning Algorithm design and analysis conferences Cloud computing

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Optimal Selection of Complex Product Manufacturing Service Suppliers Based on Blockchain Technology

Optimal Selection of Complex Product Manufacturing Service S...

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Computer science and Blockchain (CCSB), international conference on

作者： Xin Guo Geng Zhang Gang Wang Yingfeng Zhang Key Laboratory of Industrial Engineering and Intelligent Manufacturing School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi PR China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

the rapid development of information technology is profoundly affecting the manufacturing industry. Compared to traditional manufacturing industry, the complex product manufacturing is of high complexity, and with large amount of manufacturing service suppliers, so complex product suppliers selection is of significant importance. this paper constructs a complex product manufacturing service suppliers selection model based on blockchain technology, providing a secure and efficient platform for information sharing and decision optimization. Moreover, a robust goal programming (RGP) method for selecting complex product manufacturing service suppliers under uncertain demand is proposed. Finally, the feasibility and effectiveness of the proposed method are verified through example.

关键词： Manufacturing industries Supply chains Decision making Information sharing programming Manufacturing Blockchains Security Information technology Optimization

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Software development as a workflow process

Software development as a workflow process

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Asia-Pacific conference on Software engineering

作者： D.K.C. Chan K.R.P.H. Leung Domaine de Voluceau INRIA Rocquencourt Le Chesnay France Department of Computing Hong Kong Polytechnic University Hung Hom China

It is a general consensus that automated support for software development is essential to harness the ever increasing complexity of today's software. Many software development models, tools, and environments have been introduced to address such a need; however they are usually methodology-specific and impose a rather authoritarian policy on the way software is developed. this paper advocates the use of workflow systems to enact the process of software development. Besides being more general and flexible, the workflow paradigm supports useful features lacking in other approaches. Also, it helps to reduce development complexity by allowing both the software development process and the software themselves to be captured using the very same paradigm. this paper introduces a workflow system being developed to support the software development process by presenting a solution to the ISPW-6 Software Process Example expressed in its specification language. this paper therefore serves two purposes: (1) to introduce a new and more general approach to software process enactment and (2) to identify new requirements for the workflow paradigm, such as event dependency, that are applicable to many other advanced applications.

关键词： programming Application software Software tools Monitoring Process control Business process re-engineering Software development management Environmental management Human resource management

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Application of Particle Swarm Optimization and Genetic Algorithm to the optimal design of CO2 gas cooler

Application of Particle Swarm Optimization and Genetic Algor...

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science and Technology Innovation (IAECST), international Academic Exchange conference on

作者： Jingyang Cai Yichun Wang Fen Guo Hongzeng Ji Xiaoyu Huang Xiuhui Duan School of Mechanical Engineering Beijing Institute of Technology Beijing China

Particle Swarm Optimization and Genetic Algorithm are bionic optimization algorithms. this paper takes CO 2 louvered micro-channel gas cooler as an example and achieves multi-objective optimization with the objective function of maximum heat exchange and minimum cost. the optimization results show that the optimized results by both Particle Swarm Optimization and Genetic Algorithm are better than before optimization, and the optimization speed of Particle Swarm Optimization is faster. So it is practical to use Particle Swarm Optimization algorithm and Genetic Algorithm to optimize the design of CO 2 louver microchannel gas cooler system

关键词： Heating systems Technological innovation Costs Heat pumps Linear programming Particle swarm optimization Optimization

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A Multi-task Learning Model for Emotion-Cause Extraction Based on Emotion Classification 1

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4th international conference on artificial Intelligence in China, AIC 2022

作者： Liu, Lu Qin, Jun Meng, Kai Liu, Jing Zhang, Zejin School of Computer Science South-Central Minzu University Wuhan430000 China Hubei Provincial Engineering Research Center for Intelligent Management of Manufacturing Enterprises Wuhan430000 China Hubei Provincial Engineering Research Center of Agricultural Blockchain and Intelligent Management Wuhan430000 China

ISBN: (数字)9789819912568

ISBN: (纸本)9789819912551

Emotion-Cause joint extraction is to extracting both the emotion and its corresponding cause from the given text, which has a wide range of application scenarios. Previous work only considered emotion extraction, cause extraction and emotion-cause relation classification tasks. this paper proposes a multi-task learning model based on emotion classification to perform emotion-cause joint extraction in a unified model, which obtains semantic features of different granularity based on Bert and attention mechanism. We also introduce focus loss function to deal with the sample imbalance problem. Experimental results show that the emotion classification subtask can effectively extract the emotional features of documents. Compared with the existing models, the experimental results show that our model outperforms the state-of-the-art model on emotion-cause joint extraction. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Extraction

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Multi-stage Robust Optimal Planning of Microgrid Clusters in the Environment of Distribution-side Electricity Market

Multi-stage Robust Optimal Planning of Microgrid Clusters in...

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Advanced Electrical and Energy Systems (AEES), international conference on

作者： Wei Chai Peikun Xie Zhenkun Li Zhiquan Zhang Electric Power Research Institute State Grid Shanghai Municipal Electric Power Company Shanghai China School of Electric Power Engineering Shanghai University of Electric Power Shanghai China

With the development of the distribution power market, an increasing number of microgrids will appear in the distribution system. In this paper, a multi-stage robust optimal planning method for microgrid clusters is proposed to solve the interest conflict between microgrid clusters and distribution system. Based on the master-slave game theory, this method establishes a two-layer programming mathematical model for the distribution network and the microgrid clusters. In the upper layer, the optimal operation model of the distribution network is established to reduce operating costs and improve the voltage level. In the lower layer, the optimal planning model for the microgrid clusters is constructed to determine the allocation and capacity of each microgrid. In addition, considering the uncertainty of load growth, the robust optimization strategy is added in our methodology to improve the robustness of the planning scheme. Because the above model is a robust optimization bi-level programming problem, the Karush-Kuhn- Tucker(KKT) condition is used to convert the original problem into a single-level equilibrium constraint mathematical programming problem, thus the programming problem can be achieved by the Column-and-Constraint Generation(C&CG) algorithm. Finally, through the analysis of IEEE-33 node, the results show that the method improves the ability of the distribution network to absorb renewable energy and the Operation Index of the distribution network, at the same time, it ensures the economic benefits of investors and effectively realizes the coordinated development of distribution network and micro-grid.

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Study on Cloud Model of Interactive programming Learning to Improve the Interest of Higher Vocational Students

Study on Cloud Model of Interactive Programming Learning to ...

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2018 4th international conference on Education,Management and Information Technology(ICEMIT 2018)

作者： Liu Xingxing Yang Chenggang Department of Information Engineering Private Sichuan Tianyi College School of Marxism Wuhan University of Technology

For the software design specialty in higher vocational college, what it mainly cultivates is the high-technology applied talents, focusing on cultivating the practical abilities of students. However, that's also the place that exists difficulty. In order to improve the enthusiasm of hands-on programming of students, in this paper, the online interactive programming learning mode based on cloud environment was proposed, which is a means for students to verify whether or not they have mastered the technology immediately after learning the knowledge by means of online programming, and a real-time interactive model that can greatly enhance hands-on practice of students. It takes advantage of overcoming a learning scenario similar to the overcoming all the difficulties in the way to allow students to carry out practical exercises unconsciously. It not only trains their actual development capabilities, but also helps teachers to better improve the quality of teaching.

关键词： cloud computing programming design specialty practical ability online interactive programming real-time feedback: improving interest

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