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IEEE Sensors

作者： Zhang Pengfei Teo Keng Boon Wang Yixin Institute for Infocomm Reserach A*STAR Infrastructure Energy and Environment Department Singapore

ISBN: (纸本)9781728116358

We develop a new sensor selection scheme in wireless sensor networks for structure health monitoring (SHM). The sensor selection method is based on cross entropy method. It can help maximize the wireless sensor network lifetime while gurantee the quality of SHM. We model the structure as Gaussian Process distributed and nodes transmit to gateway (GW). Through extensive simulations, we show that our method outperforms the benchmark method which make it suitable for real experiment setting.

关键词： Wireless Sensor Networks Sensor selection Structure Health Monitoring Gaussian process cross-entropy method Wireless sensor networks cross entropy structural monitoring Gaussian processes Simple harmonic motion Sensors HEALTH MONITORING

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Reliability Evaluation for Microgrids Using cross-entropy Monte Carlo Simulation

Reliability Evaluation for Microgrids Using Cross-Entropy Mo...

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IEEE International Conference on Probabilistic methods Applied to Power Systems (PMAPS)

作者： Hanna, Ryan Disfani, Vahid R. Kleissl, Jan Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA 92093 USA IIASA Laxenburg Austria Univ Tennessee Dept Elect Engn Chattanooga TN 37403 USA

ISBN: (纸本)9781538635964

This paper proposes a new method to evaluate reliability indices for load served within a grid-connected microgrid. It is based on sequential Monte Carlo simulation (MCS) and the cross-entropy method;considers time-dependent generating resources, load, and energy storage;and calculates the probability, frequency, and cost of loss of load events. Grid-connected microgrids are typically very reliable systems, and thus sequential MCS methods can face slow convergence times. The cross-entropy method, which is used here to distort transition rates for the distribution system and generators, greatly speeds convergence without sacrificing the primary advantages of sequential simulation. Validation is run against sequential MCS for several microgrid configurations. The new algorithm reproduces indices to within 6% and reduces run-times by factors of 5-19.

关键词： cross-entropy method distributed energy resource loss of load rare event reliability assessment risk analysis

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Hierarchical Decision-Modeling Framework to Meet Environmental Objectives in Biofuel Development

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2018年第7期144卷 1-15页

作者： Shafiee-Jood, Majid Housh, Mashor Cai, Ximing Univ Illinois Dept Civil & Environm Engn Ven Te Chow Hydrosyst Lab 205N Mathews Ave Urbana IL 61801 USA Univ Haifa Fac Management Dept Nat Resources & Environm Management IL-31905 Haifa Israel

Biofuel development to comply with the Renewable Fuel Standard (RFS) would alter conventional crop patterns in agricultural watersheds. As a result, the hydrologic response of the watersheds will exhibit different and often opposing effects on agrohydrological system variables such as riverine nitrate-N load and streamflow. Conventional modeling approaches treat those externalities as regulatory constraints, often fail to consider the hierarchical nature of the decision-making process, and end with unrealistic solutions. This study therefore proposes an alternative decision-modeling framework for biofuel development to optimize a water-quality objective under different levels of streamflow requirement in the watershed. A bilevel programming model is established to mimic the hierarchical decision-making process in environmental regulation. The model is applied to the Sangamon River basin, a typical agricultural watershed in central Illinois, to determine the optimal locations and type of ethanol biorefineries as policy instruments. The results show that the proposed instruments can effectively guide the decisions in biofuel development to meet the environmental objectives in the watershed, although adopting the proposed framework yields a lower profit than the conventional models, which is the price of a more realistic solution to the hierarchical decision problem. The results also highlight the importance of spatial heterogeneity and identifying an appropriate spatial scale to design effective environmental policies in biofuel development.

关键词： Biofuel development Bilevel programming Environmental regulation Permits cross-entropy method

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Evaluation of recent hydro-climatic changes in four tributaries of the Niger River Basin (West Africa)

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HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES 2017年第5期62卷 715-728页

作者： Badou, Djigbo Felicien Kapangaziwiri, Evison Diekkrueger, Bernd Hounkpe, Jean Afouda, Abel Univ Abomey Calavi West African Sci Serv Ctr Climate Change & Adapte Grad Res Programme Climate Change & Water Resourc Cotonou Benin CSIR Nat Resources & Environm Hydrosci Res Grp Pretoria South Africa Univ Bonn Dept Geog Bonn Germany

West Africa experienced severe drought during the 1970s and 1980s, posing a threat to water resources. A wetter climate more recently suggests recovery from the drought. The Mann-Kendall trend and Theil-Sen's slope estimator were applied to detect probable trends in weather elements in four sub-basins of the Niger River Basin between 1970 and 2010. The cross-entropy method was used to detect breakpoints in rainfall and runoff, Spearman's rank test for correlation between the two, and cross-correlation analysis for possible lags. Results showed an overall increase in rainfall and runoff and a decrease in sunshine duration. Spearman's coefficients suggest significant (5%) moderate to strong rainfall-runoff correlation for three sub-basins. A significant lower runoff was observed around 1979, with a rainfall break around 1992, indicating possible cessation of the drought. Temperatures increased significantly, at 0.02-0.05 degrees C year(-1), with a negative wind speed trend for most stations. Half of the stations exhibited an increase in potential evapotranspiration.

关键词： Climate variability climate trends breakpoint analysis cross-entropy method Benin

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Improved Importance Sampling for Reliability Evaluation of Composite Power Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第3期32卷 2426-2434页

作者： Tomasson, Egill Soder, Lennart KTH Royal Inst Technol Integrat Renewable Energy Sources Grp S-11428 Stockholm Sweden

This paper presents an improved way of applying Monte Carlo simulation using the crossentropy method to calculate the risk of capacity deficit of a composite power system. By applying importance sampling for load states in addition to the generation and transmission states in a systematic manner, the proposed method is many orders of magnitude more efficient than the crude Monte Carlo simulation and considerably more efficient than other crossentropy-based algorithms that apply other ways of estimating the importance sampling distributions. An effective performance metric of system states is applied in order to find optimal importance sampling distributions during presimulation that significantly reduces the required computational effort. Simulations, using well-known IEEE reliability test systems, show that even problems that are nearly intractable using crude Monte Carlo simulation become very manageable using the proposed method.

关键词： EPNS importance sampling LOLP Monte Carlo simulation power system reliability cross-entropy method

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Hierarchical earthquake shelter planning in urban areas: A case for Shanghai in China

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2017年 22卷 431-446页

作者： Li, Huiyong Zhao, Laijun Huang, Rongbing Hu, Qingmi Shanghai Univ Sch Management Shanghai 200444 Peoples R China Shanghai Jiao Tong Univ Sino US Global Logist Inst Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Antai Coll Econ & Management Shanghai 200030 Peoples R China York Univ Sch Adm Studies 4700 Keele St Toronto ON M3J 1P3 Canada

Proper pre-disaster emergency shelter locations and the corresponding victim allocation contribute to mitigating disaster loss in densely populated urban areas. The number of victims and their needs in emergency shelters change over the duration of the post-earthquake period, as evidenced by both actual earthquake records and theoretical analysis. To match the time-varying demand with the shelter planning, the hierarchical shelters that provide different level services should be projected. We first estimate the varying number of the victims in shelters during the post-earthquake period, and then model the locations for emergency shelters with a nested hierarchy, and also model the allocation of victims among shelters. Furthermore, we employ an efficient hybrid cross-entropy method to solve the location model and develop a better victim allocation scheme with a swap move to overcome the drawbacks of other allocation schemes. The empirical results from application to the Xuhui District in Shanghai of China show that emergency shelter planning based on a time-varying demand can reduce the construction cost of shelters and the averaged evacuation distance traveled by the victims, compared to the current policy based on the unvarying demand.

关键词： Emergency shelter planning Earthquake Refuge demand Shelter service cross-entropy method

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Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

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EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS 2017年第10期226卷 2393-2406页

作者： Anisimov, D. N. Thai Son Dang Banerjee, Santo The Anh Mai Moscow Power Engn Inst Dept Control & Informat Moscow Russia Vinh Univ Dept Elect & Telecommun Nghe An Vietnam Univ Putra Malaysia Inst Math Res Serdang Malaysia

In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a cross-entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

关键词： ROBOTS cross-entropy method entropy OPERATING systems (Computers) PARAMETERS (Statistics)

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Fast reconstruction of computerized tomography images based on the cross-entropy method

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FLOW MEASUREMENT AND INSTRUMENTATION 2011年第4期22卷 295-302页

作者： Wang, Qi Wang, Huaxiang Yan, Yong Tianjin Univ Sch Elect Engn & Automat Tianjin 300072 Peoples R China Univ Kent Sch Engn & Digital Arts Canterbury CT2 7NT Kent England

Computerized tomography (CT) has been applied to multi-phase flow measurement in recent years. Image reconstruction of CT often involves repeatedly solving large-dimensional matrix equations, which are computationally expensive, especially for the case of on-line flow regime identification. In this paper, a minimum cross-entropy (MCE) reconstruction based on wavelet multi-resolution processing, i.e., an MRMCE method, is proposed for fast reconstruction of CT images. Each row of the system's matrix is transformed by 1-D wavelet decomposition. A regularized MCE solution is obtained using the simultaneous multiplicative algebraic reconstruction technique (SMART) at a coarse resolution level, where important information of the reconstructed image is contained. Then the solution in the finest resolution is obtained by inverse fast wavelet transformation (IFWT). Both computer simulation and experimental work were carried out for oil-gas two-phase flow regimes. Results obtained indicate that the MRMCE method improves the resolution of the reconstructed images and dramatically reduces the computation time compared with the traditional linear back-projection (LBP), MCE and algebraic reconstruction technique (ART) methods. Furthermore, the new method can also be used to accurately estimate the local time-averaged void fraction of dynamic two-phase flow. It is suitable for on-line multi-phase flow measurement. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Computerized tomography (CT) cross-entropy method Image reconstruction Multi-resolution decomposition Two-phase flow Wavelet transform

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Cooperative cross-entropy method for generating entangled networks

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ANNALS OF OPERATIONS RESEARCH 2011年第1期189卷 205-214页

作者： Hui, Kin-Ping Def Sci & Technol Org Edinburgh SA Australia

Survivability is rapidly becoming an important criterion in network design and planning. This is due to our increased dependence on ever more complex communication networks. Another important criterion which plays a central role in design and planning decisions is cost. As a result, network planners tend to design sparse networks to minimise cost. There is a class of networks known as entangled networks which seems to satisfy both criteria of survivability and sparseness. In this paper, we demonstrate how the cross-entropy method may be utilised to generate entangled networks. We also propose a cooperative optimisation approach to further improve the generation of an optimal entangled network.

关键词： cross-entropy method Combinatorial optimisation Cooperative optimisation Entangled networks Survivable networks

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Estimating change-points in biological sequences via the cross-entropy method

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ANNALS OF OPERATIONS RESEARCH 2011年第1期189卷 155-165页

作者： Evans, G. E. Sofronov, G. Y. Keith, J. M. Kroese, D. P. Univ Queensland Dept Math Brisbane Qld 4072 Australia Univ Wollongong Sch Math & Appl Stat Wollongong NSW 2522 Australia Queensland Univ Technol Sch Math Sci Brisbane Qld 4001 Australia Monash Univ Sch Math Sci Clayton Vic 3800 Australia

The genomes of complex organisms, including the human genome, are known to vary in GC content along their length. That is, they vary in the local proportion of the nucleotides G and C, as opposed to the nucleotides A and T. Changes in GC content are often abrupt, producing well-defined regions. We model DNA sequences as a multiple change-point process in which the sequence is separated into segments by an unknown number of change-points, with each segment supposed to have been generated by a different process. Multiple change-point problems are important in many biological applications, particularly in the analysis of DNA sequences. Multiple change-point problems also arise in segmentation of protein sequences according to hydrophobicity. We use the cross-entropy method to estimate the positions of the change-points. Parameters of the process for each segment are approximated with maximum likelihood estimates. Numerical experiments illustrate the effectiveness of the approach. We obtain estimates of the locations of change-points in artificially generated sequences and compare the accuracy of these estimates with those obtained via other methods such as IsoFinder (Oliver et al. in Nucl. Acids Res. 32:W283-W292, 2004) and Markov Chain Monte Carlo. Lastly, we provide examples with real data sets to illustrate the usefulness of our method.

关键词： ORGANISMS HUMAN genome DNA NUCLEOTIDE sequence CHANGE-point problems cross-entropy method AMINO acids

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