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3rd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)

作者： Cui, Junjie BASIS Int Sch Guangzhou Guangzhou Peoples R China

ISBN: (纸本)9781665417907

A* search or other nonuniform-cost searching algorithms are always combined with samplebased planners, such as probabilistic roadmap planner (PRM), to solve 2D navigation problems. However, the combination of uniform-cost searching algorithms and sample-based planners in solving these problems was not fully explored in the past. In this study, programs were implemented to allow the combination of PRM with A* search, breadth-first search, and depth-first search. After the searching algorithms were implemented, experiments were done to test the completeness, optimality, and time of the combinations of the algorithms. In the experiments, the programs were required to find a path for a robot to navigate from the start point to the endpoint in a 2D map with obstacles. This work found that the combination of PRM with A* search was not always complete, but the combinations of PRM with breadth-first search and depth-first search were always complete. After comparing the path planned by three different algorithms, it was determined that the combinations of PRM with breadth-first search and depth-first search were not always optimal, especially when the number of sample points was large. Consequently, A* search is still the most suitable searching algorithm for sample-based planners. This study well explained the shortcomings of combining uniform-cost search algorithms with sample-based planners.

关键词： robot navigation automated planning planning algorithms searching algorithms

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Analysis of radix searching of exponential bidirectional associative memory

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IEE PROCEEDINGS-COMPUTERS AND DIGITAL TECHNIQUES 1998年第4期145卷 279-285页

作者： Wang, CC Tsai, CF Lee, JP Natl Sun Yat Sen Univ Inst Elect Engn Kaohsiung 80424 Taiwan

The exponential bidirectional associative memory (eBAM) is a high-capacity associative memory. However, in the hardware realisation of eBAM, increasing efforts have been made to obtain an optimally small radix of exponential circuit for the fixed dynamic range of the VLSI circuit transistor, thereby allowing the dimension of the stored patterns to reach maximum. In this paper, the authors prove the stability of eBAM. The absolute lower bound of the radix of the eBAM is also obtained. In addition, an algorithm is presented to compute the optimal radix of an exponential circuit. To preserve the optimality of the radix, an algorithm capable of updating the radix when new pattern pairs are to be installed is proposed. Moreover, a deterministic method is presented to train and install pattern pairs with a predetermined fault tolerance ability.

关键词： bidirectional associative memory (BAM) signal-to-noise ratio (SNR) exponential BAM searching algorithms stability

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A PARALLEL ALPHA/BETA TREE searching ALGORITHM

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PARALLEL COMPUTING 1989年第3期10卷 299-308页

作者： HYATT, RM SUTER, BW NELSON, HL UNIV CALIF LAWRENCE LIVERMORE NATL LAB CTR COMPUTATLIVERMORECA 94550

This paper gives a theoretical foundation for using parallel processing to search an alpha/beta minimax game tree. A mathematical discussion predicts the behavior of a particular parallel algorithm, Principle Variation Splitting (PVS), along with an enhancement that improves performance for most test cares. After the theoretical discussion, some practical results obtained by running two implementations of the PVS algorithm on a 30-processor tightly coupled shared memory machine are given to show the speedup obtained by parallel processing.

关键词： searching algorithms alpha/beta algorithm Principle Variation Splitting (PVS) speedup by parallel processing

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OPTIMAL DYNAMIZATION OF DECOMPOSABLE searching PROBLEMS

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INFORMATION PROCESSING LETTERS 1981年第2期12卷 93-98页

作者： MEHLHORN, K OVERMARS, MH RIJKSUNIV UTRECHT VAKGRP INFORMAT3508 TA UTRECHTNETHERLANDS

Several efforts have been made to develop general methods for turning static solutions to problems into dynamic ones. Earlier researchers made the important observation that a general approach to ''dynamization'' is especially relevant to the class of so-called decomposable searching problems. A general method of dynamization is examined, along with the question of optimality.

关键词： searching algorithms complexity dynamization

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Evaluation of a spectral searching algorithm for the comparison of Raman band positions

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SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2011年第1期80卷 27-31页

作者： Vandenabeele, Peter Univ Ghent Dept Archaeol B-9000 Ghent Belgium

Raman spectroscopic identification of unknown materials involves often the comparison of the spectrum of the unknown spectrum with previously recorded reference spectra or data from literature. However, when spectra with many Raman bands or spectra of mixtures are involved, searching can be quite complex. Different chemometrical approaches have been proposed, but these have some drawbacks. Therefore, in this paper a novel approach is proposed, which is based on a multivariate comparison of Raman band positions. Different similarity measures can be used and are evaluated with spectra of test samples that were recorded on different spectrometers, using different laser wavelengths. Moreover, this study evaluates the performances of this algorithm for identifying different compounds in mixtures, by using an iterative approach. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Raman spectroscopy Spectral identification Mixtures searching algorithms

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Application of Binary searching for Item Exposure Control in Cognitive Diagnostic Computerized Adaptive Testing

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APPLIED PSYCHOLOGICAL MEASUREMENT 2017年第7期41卷 561-576页

作者： Zheng, Chanjin Wang, Chun Jiangxi Normal Univ Nanchang Jiangxi Peoples R China Univ Minnesota Minneapolis MN USA

Cognitive diagnosis has emerged as a new generation of testing theory for educational assessment after the item response theory (IRT). One distinct feature of cognitive diagnostic models (CDMs) is that they assume the latent trait to be discrete instead of continuous as in IRT. From this perspective, cognitive diagnosis bears a close resemblance to searching problems in computer science and, similarly, item selection problem in cognitive diagnostic computerized adaptive testing (CD-CAT) can be considered as a dynamic searching problem. Previously, item selection algorithms in CD-CAT were developed from information indices in information science and attempted to achieve a balance among several objectives by assigning different weights. As a result, they suffered from low efficiency from a tug-of-war competition among multiple goals in item selection and, at the same time, put an undue responsibility of assigning the weights for these goals by trial and error on users. Based on the searching problem perspective on CD-CAT, this article adapts the binary searching algorithm, one of the most well-known searching algorithms in searching problems, to item selection in CD-CAT. The two new methods, the stratified dynamic binary searching (SDBS) algorithm for fixed-length CD-CAT and the dynamic binary searching (DBS) algorithm for variable-length CD-CAT, can achieve multiple goals without any of the aforementioned issues. The simulation studies indicate their performances are comparable or superior to the previous methods.

关键词： CD-CAT searching algorithms binary searching restrictive progressive (RP) method restrictive threshold (RT) method SHTVOR

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Evaluation of a spectral searching algorithm for the comparison of Raman band positions

Evaluation of a spectral searching algorithm for the compari...

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9th International Conference on the Application of Raman Spectroscopy to the Earth Sciences - Sensu Latu

作者： Vandenabeele, Peter Univ Ghent Dept Archaeol B-9000 Ghent Belgium

关键词： Raman spectroscopy Spectral identification Mixtures searching algorithms

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The optimization for the backward-facing step flow control with synthetic jet based on experiment

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EXPERIMENTAL THERMAL AND FLUID SCIENCE 2015年 64卷 94-107页

作者： Xu, Fang Gao, Zhenghong Ming, Xiao Xia, Lu Wang, Yuhang Sun, Wei Ma, Rui Northwestern Polytech Univ Natl Key Lab Aerodynam Design & Res Xian 710072 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Aeronaut & Astronaut Nanjing 210016 Jiangsu Peoples R China

Active flow control, which has great application prospects in aerodynamic design, can restrain flow separation and reduce drag. In this paper, a newly developed synthetic jet device with non-linear oscillation of the reciprocating piston actuator into the pipe is introduced and applied to control flow field of backward-facing step. An in-looped design optimization system based on experimental data adopting hybrid searching algorithm is constructed and applied to optimize parameters of this synthetic jet device. The optimum state based on experiment restrains separation dramatically, which validates the efficiency of the design optimization strategy and the excellent performance of synthetic jet device. The optimum jet slot angle is 127.5 degrees and the optimum frequency is 35 Hz. Then, power consumed in driving reciprocator is considered to derive a multi-objective optimum scheme. With theoretical analysis and experimental data of velocity profiles and Reynolds stress distributions, flow control mechanism of synthetic jet device is preliminarily revealed. The optimization process and the analysis of optimum state provide guidance to the design of active flow control devices. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Flow control Design optimization Wind tunnel testing Synthetic jet searching algorithms Backward-facing step

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Analysis of the Expected Number of Bit Comparisons Required by Quickselect

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ALGORITHMICA 2010年第3期58卷 730-769页

作者： Fill, James Allen Nakama, Takehiko Johns Hopkins Univ Dept Appl Math & Stat Baltimore MD 21218 USA

When algorithms for sorting and searching are applied to keys that are represented as bit strings, we can quantify the performance of the algorithms not only in terms of the number of key comparisons required by the algorithms but also in terms of the number of bit comparisons. Some of the standard sorting and searching algorithms have been analyzed with respect to key comparisons but not with respect to bit comparisons. In this paper, we investigate the expected number of bit comparisons required by Quickselect (also known as Find). We develop exact and asymptotic formulae for the expected number of bit comparisons required to find the smallest or largest key by Quickselect and show that the expectation is asymptotically linear with respect to the number of keys. Similar results are obtained for the average case. For finding keys of arbitrary rank, we derive an exact formula for the expected number of bit comparisons that (using rational arithmetic) requires only finite summation (rather than such operations as numerical integration) and use it to compute the expectation for each target rank.

关键词： Quickselect Find searching algorithms Asymptotics Average-case analysis Key comparisons Bit comparisons

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NEW FORMULATION AND IMPROVEMENTS OF THE NEAREST-NEIGHBOR APPROXIMATING AND ELIMINATING SEARCH ALGORITHM (AESA)

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PATTERN RECOGNITION LETTERS 1994年第1期15卷 1-7页

作者： VIDAL, E Departamento de Sistemas Informáticos y Computación Universidad Politécnica de Valencia Valencia Spain

Recently, the Approximating and Eliminating Search Algorithm (AESA) was introduced to search for Nearest Neighbours in asymptotically constant average time complexity. In this paper, a new development of the AESA is presented which formally adheres to the general algorithmic strategy of (best-first) Branch and Bound (B&B). This development naturally suggests a new selection or Approximating Criterion which: (a) is cheaper to compute, (b) significantly reduces the 'overhead' or computation not alloted to distance computation, (c) leads to a more compact and clear presentation of the AESA, and (d) slightly but consistently reduces the average number of required distance computations. Experimental evidence assessing the last mentioned improvement is presented.

关键词： NEAREST NEIGHBORS POINT LOCATION METRIC TRIANGLE INEQUALITY PATTERN RECOGNITION BRANCH AND BOUND searching algorithms

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