D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy ***,the ma...
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D-S evidence theory,as a general framework for reasoning with uncertainty,allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy ***,the mass assignments given by unknown information sources are *** to measure the difference between the mass assignments has aroused people’s *** this paper,inspired by the information volume,a novel distance-based measure is proposed to measure the difference between mass *** method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass *** the same time,it is verified that the measure not only meets the properties of distance,but also proves the superiority of the proposed Information Volume Distance(IVD)through simulation ***,in the process of information fusion,the reliability of each source could be quantified through ***,based on IVD,a new multi-source information algorithm is proposed to solve the problem of multi-source information ***,algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.
There is a growing demand for time series data analysis in industry *** loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O *** User-Defined Functions(UDF)provided,com...
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There is a growing demand for time series data analysis in industry *** loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O *** User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB *** satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache *** library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,*** enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability *** provides a framework for users to examine loT time series with data quality *** show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.
Multivariate Time Series(MTS)forecasting is an essential problem in many *** forecasting results can effectively help in making *** date,many MTS forecasting methods have been proposed and widely ***,these methods ass...
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Multivariate Time Series(MTS)forecasting is an essential problem in many *** forecasting results can effectively help in making *** date,many MTS forecasting methods have been proposed and widely ***,these methods assume that the predicted value of a single variable is affected by all other variables,ignoring the causal relationship among *** address the above issue,we propose a novel end-to-end deep learning model,termed graph neural network with neural Granger causality,namely CauGNN,in this *** characterize the causal information among variables,we introduce the neural Granger causality graph in our *** variable is regarded as a graph node,and each edge represents the casual relationship between *** addition,convolutional neural network filters with different perception scales are used for time series feature extraction,to generate the feature of each ***,the graph neural network is adopted to tackle the forecasting problem of the graph structure generated by the *** benchmark datasets from the real world are used to evaluate the proposed CauGNN,and comprehensive experiments show that the proposed method achieves state-of-the-art results in the MTS forecasting task.
To recover pure speech from observed speech, this paper presents a time-domain multi-channel Wiener filter speech enhancement algorithm for the distributed speech model. For reducing the noise from noisy speech in tim...
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Membrane algorithm has been used to solve many optimization problems since it was put forward. These methods used the membrane algorithm as a container for other algorithms to solve many problems, such as, traveling s...
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Automated code generation is a powerful technique for software development, which can significantly reduce developers' effort and time for writing code. Recently, OpenAI's large language model ChatGPT has emer...
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The next Point-of-interest (POI) recommendation task is to predict the next POI that users may be interested in. POI check-in sequence implicitly reflects the user's location transition patterns, and the sequence ...
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Area has become one of the main bottlenecks restricting the development of integrated circuits. The area optimization approaches of existing XNOR/OR-based mixed polarity Reed-Muller(MPRM) circuits have poor optimizati...
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Area has become one of the main bottlenecks restricting the development of integrated circuits. The area optimization approaches of existing XNOR/OR-based mixed polarity Reed-Muller(MPRM) circuits have poor optimization effect and efficiency. Given that the area optimization of MPRM logic circuits is a combinatorial optimization problem, we propose a whole annealing adaptive bacterial foraging algorithm(WAA-BFA), which includes individual evolution based on Markov chain and Metropolis acceptance criteria, and individual mutation based on adaptive probability. To address the issue of low conversion efficiency in existing polarity conversion approaches, we introduce a fast polarity conversion algorithm(FPCA). Moreover, we present an MPRM circuits area optimization approach that uses the FPCA and WAA-BFA to search for the best polarity corresponding to the minimum circuits area. Experimental results demonstrate that the proposed MPRM circuits area optimization approach is effective and can be used as a promising EDA tool.
Ensuring the quality and conciseness of method names is pivotal for the readability and maintainability of source code. However, for developers, it often presents challenges, particularly during the course of code evo...
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Functional code clone detection is important for software maintenance. In recent years, deep learning techniques are introduced to improve the performance of functional code clone detectors. By representing each code ...
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