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Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets

Investigating the effect of different GP algorithms on the n...

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IEEE Symposium on Computational Intelligence for Financial engineering and Economics

作者： Kampouridis, Michael Chen, Shu-Heng Tsang, Edward School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park CO4 3SQ United Kingdom AI-Econ Center Department of Economics National Cheng Chi University 11623 Taiwan Centre for Computational Finance and Economic Agents University of Essex Wivenhoe Park CO4 3SQ United Kingdom

ISBN: (纸本)9781424499342

This paper extends a previous market microstructure model, where we used Genetic Programming (GP) as an inference engine for trading rules, and Self Organizing Maps as a clustering machine for those rules. Experiments in that work took place under a single financial market and investigated whether its behavior is non-stationary or cyclic. Results showed that the market's behavior was constantly changing and strategies that would not adapt to these changes, would become obsolete, and their performance would thus decrease over time. However, because experiments in that work were based on a specific GP algorithm, we are interested in this paper to prove that those results are independent of the choice of such algorithms. We thus repeat our previous tests under two more GP frameworks. In addition, while our previous work surveyed only a single market, in this paper we run tests under 10 markets, for generalization purposes. Finally, we deepen our analysis and investigate whether the performance of strategies, which have not co-evolved with the market, follows a continuous decrease, as it has been previously suggested in the agent-based artificial stock market literature. Results show that our previous results are not sensitive to the choice of GP. Strategies that do not co-evolve with the market, become ineffective. However, we do not find evidence for a continuous performance decrease of these strategies. © 2011 IEEE.

关键词： Genetic programming

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Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets

Investigating the effect of different GP algorithms on the n...

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Proceedings of the IEEE/IAFE Computational Intelligence for Financial engineering (CIFEr)

作者： Michael Kampouridis Shu-Heng Chen Edward Tsang School of Computer Science and Electronic Engineering University of Essex UK AI-Econ Center Department of Economics National Chengchi University Taiwan Centre of Computational Finance and Economic Agents University of Essex UK

关键词： Dinosaurs Timing Genetic programming Moment methods Clustering algorithms Radio frequency Self organizing feature maps

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Velocity-based reinitialisation approach in Particle Swarm Optimisation for feature selection

Velocity-based reinitialisation approach in Particle Swarm O...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Shuzlina Abdul-Rahman Zeti-Azura Mohamed-Hussein Azuraliza Abu Bakar Faculty of Computer & Mathematical Sciences Universiti Teknologi MARA Malaysia DMO Research Group FTSM Selangor School of Biosciences & Biotechnology Faculty of Science & Technolog UKM Bangi Selangor Malaysia Faculty of Science & Technology School of Biosciences & Biotechnology Selangor MALAYSIA FTSM Data Mining and Optimization Research Group Center for AI Technology Selangor MALAYSIA

Particle Swarm Optimisation (PSO) algorithm is known to be better than Genetic Algorithm (GA) as fewer operators are needed in its algorithm. However, it still has some weaknesses such as immature convergence; a condition whereby PSO tends to get trapped in a local optimum. This condition prevents them from being converged towards a better position. Various techniques have been proposed to tackle this problem by many means. This paper attempts to integrate several velocity-based reinitialisation (VBR) approaches in PSO for solving feature selection problem. Five benchmark datasets of various features dimension were used to implement the approaches. The results were analysed based on classifier performance and the selected number of features. The findings show that the proposed VBR is generally significantly better than the existing VBR approaches.

关键词： Particle swarm optimization Accuracy Optimization Convergence Genetic algorithms Machine learning Classification algorithms

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On the security of a certificateless signature scheme

On the security of a certificateless signature scheme

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2010 2nd International Conference on Signal Processing Systems, ICSPS 2010

作者： Miao, Songqin Zhang, Futai Zhang, Lei School of Computer Science and Technology Nanjing Normal University Nanjing China Jiangsu Engineering Research Center on Information Security and Privacy Protection Technology Nanjing China UNESCO in Data Privacy Department of Computer Engineering and Mathematics Universitat Rovira i Virgili Av. Països Catalans 26 E-43007 Tarragona Catalonia Spain

ISBN: (纸本)9781424468911

Certificateless public key cryptography (CLPKC) eliminates certificate management in traditional public key infrastructure and solves the problem of the key escrow in identity-based cryptography. Certificateless signature is one of the most important primitives in CLPKC. Many certificateless signature (CLS) schemes have been proposed these years. For a CLS scheme to be secure, it should be resistant to the attacks of both Type I Adversary and Type II Adversary. In this paper, we give cryptanalysis to a recently proposed certificateless signature scheme. We show it is insecure against a Type II adversary who models a malicious-but-passive key generation center (KGC). An attack is described which reveals that a Type II adversary can successfully forge a certificateless signature of any signer upon obtaining two valid signatures of that signer. © 2010 IEEE.

关键词： Authentication

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Identifying gene functions using functional expression profiles obtained by voxelation 10

Identifying gene functions using functional expression profi...

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Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology

作者： An, Li Smith, Desmond J. Xie, Hongbo Megalooikonomou, Vasileios Obradovic, Zoran Dept. of Computer and Information Sciences Data Engineering Laboratory Temple University 1805 N. Broad St. Philadelphia PA 19122 United States Department of Molecular and Medical Pharmacology David Geffen School of Medicine UCLA CHS Los Angeles CA 90095 United States Center for Information Science and Technology Temple University 303 Wachman Hall 1805 N. Broad St. Philadelphia PA 19122 United States Center for Information Science and Technology Data Engineering Laboratory Temple University 1805 N. Broad St. Philadelphia PA 19122 United States

ISBN: (纸本)9781450304382

Gene expression profiles have been widely used in functional genomic studies. However, not much work in traditional gene expression profiling takes into account the location information of a gene's expressions in the brain. Gene expression maps, which contain spatial information regarding the expression of genes in mice?s brain, are obtained by combining voxelation and microarrays. Based on the idea that genes with similar gene expression maps may have similar gene functions, we propose an approach to identify gene functions. A gene function can potentially be associated with a specific gene expression profile. We name this specific gene expression profile, Functional Expression Profile (FEP). A functional expression profile can be obtained either by directly finding genes with a certain function, or by analyzing clusters of genes that have similar expression maps and similar functions. By taking advantage of the identified FEPs, we can annotate gene functions with high accuracy. Compared to the traditional K-nearest neighbor method, our approach shows higher accuracy in predicting functions. The images of FEPs are in good agreement with anatomical components of mice?s brain, and provide valuable insight in terms of function prediction to biological scientists. Copyright © 2010 ACM.

关键词： Gene expression

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Disturbance rejection on critical resonant mode in hard disk drives

Disturbance rejection on critical resonant mode in hard disk...

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Asia-Pacific Magnetic Recording Conference (APMRC)

作者： Gangquan Dai Fan Hong Chee Khiang Pang Masaki Nagashima Department of Electrical and Computer Engineering National University of Singapore Singapore Data Storage Institute Agency for Science Technology and Research Singapore Naval Postgraduate School Spacecrali Research and Design Center Monterrey CA USA

In this paper, we propose a control method which combines notch filter and peak filter to provide disturbance rejection at the frequency of critical resonant mode. The settling rate is also improved by time-varying the parameters of the peak filter. Our simulation and experimental results show that the out-of-phase resonant mode is reshaped to an in-phase mode, and the disturbance at the frequency of critical resonant mode is attenuated by 70% with an improved settling rate. The proposed control method is shown to be robust against ± 10% perturbation of natural frequencies.

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High-order concept discovery in functional brain imaging

High-order concept discovery in functional brain imaging

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IEEE International Symposium on Biomedical Imaging

作者： Michael Barnathan Vasileios Megalooikonomou Christos Faloutsos Feroze B. Mohamed Scott Faro Data Engineering Laboratory (DEnLab) Center for Information Science and Technology Temple University Philadelphia PA USA School of Computer Science Carnegie Mellon University Pittsburgh PA USA Department of Radiology Temple University Philadelphia PA USA

ISBN: (纸本)9781424441259;9781424441266

Many spatiotemporal medical image datasets exhibit “high-order” structure, in which many independent variables exist (e.g. space and time) or features are not scalar at all. We analyze these datasets as tensors (high-order generalizations of matrices), preprocessing our dataset using wavelets to improve efficiency and performing latent concept discovery using parallel factor analysis. Both our method and naive tensor approaches discovered concepts representing handedness in an 11 subject motor task fMRI dataset. However, our method compressed the dataset by 98% and completed in 2 hours vs. 8 days, suggesting that a wavelet and tensor approach gains the benefits of high-order analysis while preserving the efficiency of low-order techniques.

关键词： Tensile stress Biomedical imaging Wavelet analysis Principal component analysis Brain modeling Image analysis Information analysis Spatiotemporal phenomena Multidimensional systems Performance analysis

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Resource management of enterprise cloud systems using layered queuing and historical performance models

Resource management of enterprise cloud systems using layere...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： David A. Bacigalupo Jano van Hemert Asif Usmani Donna N. Dillenberger Gary B. Wills Stephen A. Jarvis School of Electronics and Computer Science University of Southampton UK Data-Intensive Research Group School of Informatics University of Edinburgh UK BRE Centre of Fire Safety Engineering School of Engineering University of Edinburgh UK IBM Thomas J. Watson Research Center Yorktown Heights NY USA High Performance Systems Group Department of Computer Science University of Warwick UK

ISBN: (纸本)9781424465330

The automatic allocation of enterprise workload to resources can be enhanced by being able to make `what-if' response time predictions, whilst different allocations are being considered. It is important to quantitatively compare the effectiveness of different prediction techniques for use in cloud infrastructures. To help make the comparison of relevance to a wide range of possible cloud environments it is useful to consider the following. 1.) urgent cloud customers such as the emergency services that can demand cloud resources at short notice (e.g. for our FireGrid emergency response software). 2.) dynamic enterprise systems, that must rapidly adapt to frequent changes in workload, system configuration and/or available cloud servers. 3.) The use of the predictions in a coordinated manner by both the cloud infrastructure and cloud customer management systems. 4.) A broad range of criteria for evaluating each technique. However, there have been no previous comparisons meeting these requirements. This paper, meeting the above requirements, quantitatively compares the layered queuing and (¿HYDRA¿) historical techniques - including our initial thoughts on how they could be combined. Supporting results and experiments include the following: i.) defining, investigating and hence providing guidelines on the use of a historical and layered queuing model; ii.) using these guidelines showing that both techniques can make low overhead and typically over 70% accurate predictions, for new server architectures for which only a small number of benchmarks have been run; and iii.) defining and investigating tuning a prediction-based cloud workload and resource management algorithm.

关键词： Resource management Clouds Delay Predictive models computer science data engineering Emergency services Disaster management Guidelines Quality of service

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Multiobjective evacuation route assignment model based on genetic algorithm

Multiobjective evacuation route assignment model based on ge...

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International Conference on Geoinformatics

作者： Qiuping Li Zhixiang Fang Qingquan Li Xinlu Zong Engineering Research Center of Spatio-Temporal Data Smart Acquisition and Application Ministry of Education of China Wuhan University of China Wuhan China Wuhan University Wuhan Hubei CN School of Computer Science and Technology Wuhan University of Technology Wuhan China

ISBN: (纸本)9781424473014

Emergency evacuation in public places becomes a research focus in recent decades. One major objective of evacuation is to maximize the efficiency of the whole evacuation system. The paper proposes a multiobjective evacuation route assignment model to plan an optimal egress route set for the individual evacuees. The three objectives in the proposed model are to minimize the total evacuation time, minimize the total travel distance of all the evacuees and minimize the congestion during the evacuation process. These objectives need to be satisfied simultaneously while some of them conflict with each other. The travel speed on each road segment is related with the time and the number of evacuees on it during a certain time period. The congestion of a road segment is modeled as the density of evacuees passing it in time and space dimensions. The evacuation route assignment problem can be treated as a combinatorial optimization problem. A multiobjective optimization model based genetic algorithm is adopted to solve the proposed evacuation routing problem. Wuhan Sport center in Wuhan city of China was taken as the experiment scenario to test the performance of the proposed algorithm. The results showed that it can provide some system optimal evacuation plans. Meanwhile, the multi-objective optimization model based genetic algorithm can produce a pareto optimal set rather than single optimal point, thus the model can give alternative strategies for the evacuation policy makers.

关键词： Optimization Biological cells Encoding Buildings Roads Cities and towns Evolutionary computation

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Incremental computation for MEDIAN cubes in what-if analysis

Incremental computation for MEDIAN cubes in what-if analysis

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Joint International Conference on Advances in data and Web Management, APWeb/WaiM 2009

作者： Xiao, Yanqin Zhang, Yansong Wang, Shan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Computer Center Hebei University Baoding Hebei 071002 China Department of Computer Science Harbin Finance College Harbin 150030 China

ISBN: (纸本)9783642006715

What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since source data must be kept in order to compute the new aggregate value when new tuples are inserted or deleted, in what-if analysis, incrementally computing a data cube for holistic aggregation functions is a difficult problem. In this paper, we adopt delta cube strategy and work area technique to incrementally compute data cube for MEDIAN function. The size of work area has important influence on the efficiency of the incremental computing. This paper optimizes the size of work area based on the number and the cardinality of dimension attributes of the cuboid. Performance study shows that our algorithms are effective over large databases. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Geometry

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