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Improving the drought monitoring capability of VHI at the global scale via ensemble indices for various vegetation types from 2001 to 2018

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WEATHER AND CLIMATE EXTREMES 2022年 35卷

作者： Zeng, Jingyu Zhang, Rongrong Qu, Yanping Bentod, Virgilio A. Zhou, Tao Lin, Yuehuan Wu, Xiaoping Qi, Junyu Shui, Wei Wang, Qianfeng Fuzhou Univ Coll Environm & Safety Engn Fuzhou 350116 Peoples R China Beijing Normal Univ Fac Geog Sci State Key Lab Earth Surface Proc & Resource Ecol Beijing 100875 Peoples R China China Inst Water Resources & Hydropower Res Res Ctr Flood & Drought Disaster Reduct Beijing 100038 Peoples R China Univ Lisbon Fac Ciencias Inst Dom Luiz P-1749016 Lisbon Portugal Univ Maryland Earth Syst Sci Interdisciplinary Ctr 5825 Univ Res Ct College Pk MD 20740 USA Pacific Northwest Natl Lab Joint Global Change Res Inst College Pk MD 20740 USA Univ Maryland College Pk MD 20740 USA

Drought is one of the most complex and harmful natural disasters. A study on the temporal and spatial patterns and the evolution of drought can provide a scientific basis for predicting drought occurrences. Based on a multi source dataset, we select a suitable control drought indicator for improving the vegetation health index (VHI), optimize its algorithm through Pearson correlation analysis, and compare the VHI performance before and after the improvement for various vegetation types. Results show that (1) the self-calibrated Palmer drought severity index is more suitable than the standardized precipitation evapotranspiration index for improving the VHI;(2) the contribution of the thermal condition index to the VHI in most parts of the world is higher than that of the vegetation condition index;(3) the enhanced VHI significantly improves the detection of vegetation drought;and (4) vegetation drought events occurring in high latitudes tend to worsen, and the response of different vegetation types to drought is significantly different. Our research presents a step forward in improving the effectiveness of the VHI in detecting vegetation drought and thus its application prospects. Furthermore, the response characteristics of various vegetation types to drought are identified, deepening our understanding of vegetation drought, which may help decision-makers and authorities to develop better mitigation and adaptation strategies to reduce losses caused by these events.

关键词： Global Vegetation drought Vegetation health index algorithm optimization Vegetation types Temporal and spatial characteristics

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Missile System Design using a Hybrid Evolving Swarm algorithm

Missile System Design using a Hybrid Evolving Swarm Algorith...

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IEEE Aerospace Conference

作者： Timothy W. Ledlow Zachary J. Kiyak Roy J. Hartfield Department of Aerospace Engineering Auburn University

ISBN: (纸本)9781479916191

A hybrid particle swarm-genetic algorithm optimization scheme was combined with Nelder and Mead's simplex method to produce an experimental hybrid method that integrates the global search capabilities of evolutionary heuristics with the highly effective localized search ability of the simplex method. This algorithm was applied to various missile design problems where the goal is to design a missile that can match the given flight trajectory. Three different flight trajectories were analyzed for this work: a 117 km trajectory, a 164 km trajectory, and a 221 km trajectory. The efficiency and effectiveness of the performance of the simplex method was compared with the performance of the same algorithm using the pattern search method as the local search routine in lieu of the simplex method. Optimizer performance was evaluated according to two criteria: (1) "fitness function" accuracy (how closely solutions are able to match a given objective function), and (2) convergence speed (how many calls to the objective function are required in order to reach an acceptable solution). The pattern search proved to be a more robust and reliable algorithm for such a large and complex solution space, as it was always able to avoid getting lost in the solution space. Conversely, the simplex method would occasionally become trapped around a bad solution, typically while traversing regions of the solution space sensitive to discontinuities formed by mixed-variable conversions.

关键词： Simplex method Solution space Objective function Pattern search missile systems trajectory FLIGHT PATHS algorithm optimization Search methods missiles

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Robust Fixed-Structure Controller Design of Electric Power Steering Systems

Robust Fixed-Structure Controller Design of Electric Power S...

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2009 American Control Conference (ACC 2009)

作者： Ahmed H. El-Shaer Sumio Sugita Masayoshi Tomizuka Department of Mechanical Engineering University of California at Berkeley Berkeley CA 94720 Mechanical Engineering University of California Berkeley CA 94720

ISBN: (纸本)9781424445233

This paper presents a two-degree-of-freedom controller structure for electric power steering systems. The controller is synthesized using a hybrid linear matrix inequality and genetic algorithms optimization. Robust stability is studied for both sector-bounded and passive uncertainties resulting in a system of linear matrix inequalities (LMIs) and a linear matrix equality (LME). This system of LMIs/LME defines a guaranteed cost H_(2) optimization subject to an H_(infinity)-norm performance as well as a strict-positive-real constraints. Experimental results involving human-in-the-loop show that the control design did satisfy the criteria for robust control and performance. Furthermore, the ease-of-tuning of the proposed controller structure makes it possible to improve the steering "feel".

关键词： controller structure controller design electrical power steering design control linear matrix inequalities Robust control Steering algorithm optimization tuning

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Optimized Stage Processing for Anomaly Detection on Numerical Data Streams: Grand Challenge 17

Optimized Stage Processing for Anomaly Detection on Numerica...

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Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems

作者： Ciprian Amariei Paul Diac Emanuel Onica Alexandru Ioan Cuza University of Iaşi Romania

ISBN: (纸本)9781450350655

The 2017 Grand Challenge focused on the problem of automatic detection of anomalies for manufacturing equipment. This paper reports the technical details of a solution focused on particular optimizations of the processing stages. These included customized input parsing, fine tuning of a k-means clustering algorithm and probability analysis using a lazy flavor of a Markov chain. We have observed in our custom implementation that carefully tweaking these processing stages at single node level by leveraging various data stream characteristics can yield good performance results. We start the paper with several observations concerning the input data stream, following with our solution description with details on particular optimizations, and we conclude with evaluation and a discussion of obtained results.

关键词： data stream processing event based systems algorithm optimization

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The Application of Inference Engine in University Course Scheduling System

The Application of Inference Engine in University Course Sch...

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2011 13th IEEE Joint International Computer Science and Information Technology Conference(JICSIT 2011)

作者： Li Jun Hebei College of Industry and Technology Shijiazhuang City,China Zhang Caihua Hebei College of Industry and Technology Shijiazhuang City,China WangXiao Hebei University of Science and Technologe Shijiazhuang City,China

The course scheduling is a dynamic combination of many factors involved in planning issues, it is to ensure that conflict does not produce a variety of teaching resources, and to meet the requirements of teachers and classroom resources, in the constraints. The inference engine use the idea of resource allocation, the course arrangement as a reasonable person on demand resource allocation, the use of forward reasoning strategy to optimize the efficiency of the algorithm.

关键词： inference engine Course Scheduling System algorithm optimization

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A New algorithm for Feature Extraction of Plant Diseases and Insect Pests Signal Based on Optimal Wavelet Packet and Non-negative Matrix Factorization

A New Algorithm for Feature Extraction of Plant Diseases and...

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2016 2nd International Conference on Electronics,Network and Computer Engineering(ICENCE 2016)

作者： Changcheng Li Shuyun Cai Laiwu Yin College of Electrical and Information Engineering Jilin Agricultural Science and Technology College College of mathematics and statistics Beihua University

Plant diseases and insect pests have similar symptoms, but it is difficult to distinguish between professional and technical personnel to identify plant diseases and insect pests. In order to accurate extraction of plant diseases and insect pests, physiological and pathological characteristics of signal, puts forward a based on lifting wavelet transform feature extraction algorithm optimization scheme, for the study of plant diseases and insect pests damage signal showing the effect of the prior farmers identify any disease, choose the correct method of governance, quickly make the right decision, improve farmers plant diseases and insect pests, harm signal feature extraction and recognition level. The simulation results show that this algorithm can be used to optimize the stability and convergence, and can be used as an ideal plant disease and insect pests signal feature extraction optimization algorithm, which can effectively identify the different plant diseases and insect pests.

关键词： Plant diseases and insect pests feature extraction optimal wavelet packet basis non-negative matrix factorization algorithm optimization

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USE OF TIGHT FRAMES FOR OPTIMIZED COMPRESSED SENSING

USE OF TIGHT FRAMES FOR OPTIMIZED COMPRESSED SENSING

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European Signal Processing Conference

作者： Evaggelia Tsiligianni Lisimachos P. Kondi Aggelos K. Katsaggelos University of Ioannina Dept. of Computer Science Northwestern University Dept. of EECS

ISBN: (纸本)9781467310680

Compressed sensing (CS) theory relies on sparse representations in order to recover signals from an under-sampled set of measurements. The sensing mechanism is described by the projection matrix, which should possess certain properties to guarantee high quality signal recovery, using efficient algorithms. Although the major breakthrough in compressed sensing results is obtained for random matrices, recent efforts have shown that CS performance could be improved with optimized non-random projections. Designing matrices that satisfy CS theoretical requirements is closely related to the construction of equiangular tight frames, a problem that has applications in various scientific fields like sparse approximations, coding, and communications. In this paper, we employ frame theory and propose an algorithm for the optimization of the projection matrix that improves sparse signal recovery.

关键词： Compressed sensing Tight frames Grassmannian Frames Signal restoration matrices TIGHT FRAMES algorithm optimization COMPRESSED Compressed sensing CONTAINMENT SPRAY carbon monosulfide Cesium Communication Research conditioned stimulus

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Maximum relevance, minimum redundancy feature extraction for hyperspectral images

Maximum relevance, minimum redundancy feature extraction for...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Mehdi Kamandar Hassan Ghassemian Faculty of Electrical and Computer Engineering Tarbiat Moalem University Tehran Iran

ISBN: (纸本)9781424467600

In this paper we propose a new feature extraction scheme for hyperspectral images based on mutual information. Relevance of extracted feature set to class label has been measured by average of mutual information between each of them and class label and Redundancy of them is measured by average of mutual information between each pair of them. Based on relevance of features and redundancy between them, we propose a cost function that maximize relevance of extracted features and simultaneously minimize redundancy between them. This cost function has been already used for feature selection. In this paper we will find the parameters of an optimal linear mapping by optimizing the proposed cost function with respect them. Linear methods are attractive due to their simplicity. Because of nonlinear and nonconvex relation between proposed cost function and the parameters, we use genetic algorithm for optimization. Mutual information accounts for higher order statistics, not just for second order as PCA and LDA do. Hence mutual information is a better criterion for hyperspectral images because they have higher order statistics than two. Our classification results for AVARIS data shows proposed method has better performance over PCA and LDA.

关键词： Hyperspectral Image Classification Feature Extraction Mutual Information And Genetic algorithm Feature extraction Cost functions hyperspectral imagery redundancy Higher order statistics laser Doppler anemometry Anterior interventricular branch of left coronary artery Left-sided displacement of abomasum algorithm optimization principal components analysis Passive Cutaneous Anaphylaxis

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An Improved Image Style Transfer algorithm Based on Deep Learning Network

An Improved Image Style Transfer Algorithm Based on Deep Lea...

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作者： Yan-ni JI Yu-de WANG Jia CHANG Qufu Noraml University School of Physics and Engineering

Aiming at the problem of local style migration distortion in image stylization, an improved image style migration algorithm based on deep learning network is proposed. Firstly, the VGGNet-19 network is used to extract the convolution layer features of images. Then the characteristics of convolution layer are analyzed, and the combination of style and content features is studied. The Block3 layer with the smallest content loss and style loss is selected for feature fusion with conv1, conv2, conv3, conv4 and conv5 layers. Finally, under the optimal combination of features, Adam algorithm is used to optimize the image style migration. The experimental results show that the proposed algorithm can effectively improve the distortion of local style migration and provide theoretical support for the implementation of style migration technology.

关键词： Feature fusion algorithm optimization Image stylization

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Design Methodology for Face Detection Acceleration

Design Methodology for Face Detection Acceleration

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Annual Conference of the IEEE Industrial Electronics Society

作者： Laurentiu Acasandrei Angel Barriga Instituto de Microelectronica de Sevilla IMSE-CNM-CSIC Instituto de Microelectronica de Sevilla/Univ. Sevilla IMSE-CNM-CSIC/Univ. Sevilla

ISBN: (纸本)9781479902255

A design methodology to accelerate the face detection for embedded systems is described, starting from algorithm optimization (high level) and ending with software and hardware codesign (low level) by addressing the issues and the design decisions made at each level based on the performance measurements and system limitations. The implemented embedded face detection system consumes very little power compared with the traditional PC software implementations while maintaining the same detection accuracy. The proposed face detection acceleration methodology is suitable for real time applications.

关键词： Face detection Embedded system Design methodology Hardware & software codesign Facial Recognition Embedded systems algorithm optimization Performance metrics acceleration

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