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OCET: One-Dimensional Convolution Embedding Transformer for Stock Trend Prediction 1

17th international conference on Bio-Inspired Computing: theories and Applications, BIC-TA 2022

作者： Yang, Peng Fu, Lang Zhang, Jian Li, Guiying Department of Statistics and Data Science Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China Shenzhen Securities Information Co. Ltd. Shenzhen China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Due to the strong data fitting ability of deep learning, the use of deep learning for quantitative trading has gradually sprung up in recent years. As a classical problem of quantitative trading, Stock Trend Prediction (STP) mainly predicts the movement of stock price in the future through the historical price information to better guide quantitative trading. In recent years, some deep learning work has made great progress in STP by effectively grasping long-term timing information. However, as a kind of real-time series data, short-term timing information is also very important, because stock trading is high-frequency and price fluctuates violently. And with the popularity of Transformer, there is a lack of an effective combination of feature extraction and Transformer in STP tasks. To make better use of short term information, we propose One-dimensional Convolution Embedding (OCE). Simultaneously, we introduce effective feature extraction with Transformer into STP problem to extract feature information and capture long-term timing information. By combining OCE and Transformer organically, we propose a noval STP prediction model, One-dimensional Convolution Embedding Transformer (OCET), to capture long-term and short-term time series information. Finally, OCET achieves a highest accuracy up to 0.927 in public benchmark FI-2010 When reasoning speed is twice that of SOTA models and a highest accuracy of 0.426 in HKGSAS-2020. Empirical results on these two datasets show that our OCET is significantly superior than other algorithms in STP tasks. Code are available at https://***/langgege-cqu/OCET. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

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BOOSTING thE MODEL DISCOVERY OF HYBRID DYNAMICAL SYSTEMS IN AN INFORMED SPARSE REGRESSION APPROACH 17

BOOSTING THE MODEL DISCOVERY OF HYBRID DYNAMICAL SYSTEMS IN ...

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ASME international Design Engineering Technical conferences / 42nd Annual Computers and Information in Engineering conference (IDETC-CIE) / 17th international conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC)

作者： Novelli, Nico Lenci, Stefano Belardinelli, Pierpaolo Polytech Univ Marche DICEA Ancona Italy

ISBN: (纸本)9780791885468

We present an efficient data-driven sparse identification of dynamical systems. the work aims at reconstructing the different sets of governing equations and identify discontinuity surfaces in hybrid systems when the number of discontinuities is known a priori. In our approach, we first focus to identify the switches between the separate vector fields. then, the dynamics among the manifolds are regressed by making use of the model discovery algorithm of Brunton et al. [1]. the reconstruction of the discontinuity surfaces comes as the outcome of a statistical analysis implemented via symbolic regression with small clusters (microclusters) and a rigid library of models. this allows to identify all the many possible switch points that are clustered to determine the actual discontinuity surfaces. the performances of the method are tested on two numerical examples, namely, a canonical spring-mass hopper and a free/impact electromagnetic energy harvester. these applications are characterized by the presence of a single and double discontinuity, respectively. the analyses demonstrate that in the supervised approach, i.e. where the number of discontinuities is preassigned, we are capable to determine accurately both discontinuities and set of governing equations. It is found a great improvement in time of computation reaching the maximum achievable reliability that outperform existing data-driven identification approaches for hybrid systems.

关键词： Dynamic systems Switches Performance computation Manifolds Springs Statistical analysis Dynamics (Mechanics) Electromagnetic radiation Reliability algorithms

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Using Simplified Slime Mould Algorithm for Wireless Sensor Network Coverage Problem 17th

Using Simplified Slime Mould Algorithm for Wireless Sensor N...

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17th international conference on Intelligent Computing, ICIC 2021

作者： Wei, Yuanye Zhou, Yongquan Luo, Qifang Bi, Jian College of Artificial Intelligence Guangxi University for Nationalities Nanning530006 China Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis Nanning530006 China

ISBN: (纸本)9783030845216

Wireless sensor network (WSN) coverage control is a study of how to maximize the network coverage to provide reliable monitoring and tracking services with guaranteed quality of service. the application of optimization algorithm is helpful to effectively control the network nodes energy, improve the perceived quality of services, and extend the network survival time. this paper presents a simplified slime mould algorithm (SSMA) for optimization WSN coverage problem. We mainly conducted thirteen groups of WSNs coverage optimization experiments, and compared with several well-known metaheuristic algorithms. From the experimental results and Wilcoxon rank sum test results demonstrate that SSMA is generally competitive, outstanding performance and effectiveness. © 2021, Springer Nature Switzerland AG.

关键词： Wireless sensor networks

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Performance Comparison of Two Generic MPC-frameworks with Symmetric Ciphers 17

Performance Comparison of Two Generic MPC-frameworks with Sy...

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17th international Joint conference on E-Business and Telecommunications (SECRYPT)

作者： Loruenser, thomas Wohner, Florian AIT Austrian Inst Technol Vienna Austria

ISBN: (纸本)9789897584466

Research on multiparty computation (MPC) made substantial progress over recent years. It can be used to protect the privacy of data and users in modern application scenarios like Blockchain and the Internet of things where different stakeholders want to collaborate. In this work we analyze practical aspects of two generic MPC frameworks, MP-SPDZ and MPyC, to generate new insights into the state-of-the art for generic and platform independent MPC. We implemented various symmetric ciphers and did extensive benchmarking on both frameworks to see how universal and generic they are and if they can be used without special knowledge. We found that the achieved performance cannot be trivially estimated from the algorithms without implementing. the stream cipher Trivium was by far the fastest and most portable in our tests. Contrary to most of existing literature we also addressed non optimal network settings and found surprising results. the asynchronous architecture of MPyC turned out to make more efficient use of the network layer in scenarios with higher network latency and loss and could even compensate for the optimizing compiler used by MP-SPDZ.

关键词： Multiparty computation Applied Cryptography Privacy Benchmarking

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Faster privacy-preserving location proximity schemes for circles and polygons

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IET INFORMATION SECURITY 2020年第3期14卷 254-265页

作者： Jarvinen, Kimmo Kiss, Agnes Schneider, thomas Tkachenko, Oleksandr Yang, Zheng Univ Helsinki Dept Comp Sci Pietari Kalmin Katu 5 Helsinki Finland Tech Univ Darmstadt Dept Comp Sci Mornewegstr 32 Darmstadt Germany Chongqing Univ Technol Sch Comp Sci & Engn Hongguan Ave 69 Chongqing Peoples R China

In the last decade, location information became easily obtainable using off-the-shelf mobile devices. this gave momentum to developing location-based services (LBSs) such as location proximity detection, which can be used to find friends or taxis nearby. LBSs can, however, be easily misused to track users, which draws attention to the need for protecting the privacy of these users. In this work, the authors address this issue by designing, implementing, and evaluating multiple algorithms for privacy-preserving location proximity (PPLP) that are based on different secure computation protocols. their PPLP protocols support both circle and polygon range queries and have runtimes from a few to some hundreds of milliseconds and bandwidth requirements from a few hundreds of bytes to one megabyte. Consequently, they are well suited for different scenarios and offer faster runtimes and savings in bandwidth and computational power as well as security improvements compared to previous PPLP schemes. In addition, the computationally most expensive parts of the PPLP computation can be precomputed in their protocols, such that the input-dependent online phase runs in just a few milliseconds.

关键词： protocols telecommunication security circles mobile devices location-based services LBS location proximity detection secure computation protocols PPLP protocols polygon range queries privacy-preserving location proximity schemes PPLP computation schemes

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A Multi-Objective Decomposition Based Evolutionary Algorithm Using Adaptive Searching Method

A Multi-Objective Decomposition Based Evolutionary Algorithm...

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international conference on computational Intelligence and Security

作者： Xiaofang Guo School of Science Xi'an Technological University Xi'an Shaanxi China

ISBN: (纸本)9781665494908

In the research of multi-objective evolutionary algorithms (MOEAs), model-based estimation of distribution algorithms (MEDAs) are one of the important branches to build probabilistic models for generating new candidate solutions. For example, inverse modeling (IM) based MOEA takes advantage of the dependencies from objective space to decision space, and constructs some Gaussian process-based regression (GPR) inverse models for creating offspring. Motivated by the idea of IM-MOEA using trained Gaussian process regression model to generate offspring, an adaptive searching approach (ASIM-MOEA) is proposed in this paper. the estimated range for locating the test input points in GPR is dynamically adjusted according to the different stage of evolution, and a greedy sampling method for choosing the new test samples is also adopted to develop the unexplored sparse area in objective space to improve the diversity. the experimental results show that the proposed strategy achieves a better performance than state-of-the-art compared algorithms.

关键词： Adaptation models Inverse problems computational modeling Estimation Evolutionary computation Gaussian processes Sampling methods

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Revenue-Sharing based computation-Resource Allocation for Mobile Blockchain

Revenue-Sharing based Computation-Resource Allocation for Mo...

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39th IEEE international conference on Computer Communications (IEEE INFOCOM)

作者： Wu, Yuan Xu, Xu Qian, Liping Ji, Bo Shi, Zhiguo Jia, Weijia Univ Macau State Key Lab Internet Things Smart City Taipa Macau Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186955

In this paper, we investigate the revenue-sharing based computation-resource allocation for mobile Blockchain, in which conventional mobile devices (i.e., the edge-computing users, EUs) can acquire computation-resources from the edge-server (ES) for increasing their chances of winning the mining game in Blockchain. Meanwhile, as a compensation to the ES, the EUs adopt the revenue-sharing mechanism by sharing parts of their respective rewards to the ES. We formulate a joint optimization of the ES's computation-resource allocation to the EUs and the EUs' revenue-sharing to the ES, with the objective of maximizing the system-reward of all EUs and the ES. Despite the non-convexity of the joint optimization problem, we propose an algorithm based on the cyclic block coordinate descent (CBCD) to solve the problem. Our algorithm decouples the original problem into two subproblems and alternatively optimizes the EUs' revenue-sharing and ES's computation-resource allocation until reaching convergence. For each subproblem, we also propose an efficient algorithm for solving it. Numerical results are provided to validate the effectiveness and efficiency of our proposed algorithms, as well as the performance advantage of our proposed revenue-sharing based computation-resource allocation for mobile Blockchain.

关键词： Resource management Optimization Games Edge computing computational modeling Linear programming

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Active Update of Mutation Matrix Adaptation for Variable Metric Evolution Strategy

Active Update of Mutation Matrix Adaptation for Variable Met...

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international conference on computational Intelligence and Security

作者： Huilin Cheng Zhenhua Li Detian Yang Shu You Xinye Cai School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Information Technology and Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781665494908

Covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful evolutionary algorithms. To improve the efficiency of CMA-ES and make sufficient use of the sampled points, we propose an active update scheme for the mutation matrix which approximates the factorization of the covariance matrix. the active update effectively reduces the variance along undesired search directions with negative weights. We design a set of symmetric weights for all the sampled points as well as a larger learning rate. We conduct extensive experiments and show that the proposed active update scheme effectively accelerates the convergence to the optimum.

关键词： Measurement Symmetric matrices Evolutionary computation computational efficiency Matrix decomposition Security Covariance matrices

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Faster Privacy-Preserving computation of Edit Distance with Moves 14th

Faster Privacy-Preserving Computation of Edit Distance with ...

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14th international conference and workshops on algorithms and computation (WALCOM)

作者： Yoshimoto, Yohei Kataoka, Masaharu Takabatake, Yoshimasa Tomohiro, I Shin, Kilho Sakamoto, Hiroshi Kyushu Inst Technol 680-4 Kawazu Iizuka Fukuoka 8208502 Japan Gakushuin Univ Toshima Ku 1-5-1 Mejiro Tokyo 1718588 Japan

ISBN: (纸本)9783030398811;9783030398804

We consider an efficient two-party protocol for securely computing the similarity of strings w.r.t. an extended edit distance measure. Here, two parties possessing strings x and y, respectively, want to jointly compute an approximate value for EDM(x, y), the minimum number of edit operations including substring moves needed to transform x into y, without revealing any private information. Recently, the first secure two-party protocol for this was proposed, based on homomorphic encryption, but this approach is not suitable for long strings due to its high communication and round complexities. In this paper, we propose an improved algorithm that significantly reduces the round complexity without sacrificing its cryptographic strength. We examine the performance of our algorithm for DNA sequences compared to previous one.

关键词： DNA sequences

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A Multi-Objective Bilevel Optimization Evolutionary Algorithm with Local Search

A Multi-Objective Bilevel Optimization Evolutionary Algorith...

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international conference on computational Intelligence and Security

作者： Weizhong Wang Hai-Lin Liu School of Mathematics and Statistics Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781665494908

the essential goal of multi-objective bilevel opti-mization algorithms is to obtain a set of solutions uniformly distributed on the upper-level PF. However, the existing algorithms first obtain solutions evenly distributed on the lower-level PF, and then select the next generation upper-level individuals from them according to their upper-level objectives. Due to the lack of the process of adjusting the lower-level vector according to the upper-level objectives, it may lead to the poor diversity of the solutions of the upper-level task, and even fail to reach the true upper-level PF. In this paper, a lower-level environment selection strategy is designed not only to ensure that the population of the upper-level task meet the lower-level optimality constraints, but also to adjust the lower-level vector according to the upper-level objectives to obtain a higher quality upper-level PF. In addition, we proposed a new upper-level reproduction strategy to improve the search efficiency of the algorithm. the proposed algorithm has been evaluated on 5 test problems with different kinds of complexities. Experimental results demonstrate the proposed lower-level environment selection strategy and reproduction strategy are effective.

关键词： Sociology Evolutionary computation Search problems Complexity theory Security Task analysis Statistics

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