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Conference on Optoelectronic Imaging and Multimedia Technology VII

作者： Li, Xiaojie Hu, Yao Shen, Tiantian Zhang, Shaohui Cao, Jie Hao, Qun Beijing Inst Technol Sch Opt & Photon Beijing Key Lab Precis Optoelect Measurement Inst Beijing 100081 Peoples R China Hunan Normal Univ Dept Elect Informat Engn Changsha 410082 Peoples R China

ISBN: (纸本)9781510639164

With the development of machine vision technology, in the process of visual navigation with images, it is necessary to match the local geometric features or global features of the images;however, the matching of local geometric features is low in accuracy and difficult to be used in tracking. In contrast, template-based global feature matching can directly use the information of the entire image, and it has high robustness to illumination variations and occlusions, so it has attracted widespread attention. At present, the classical matching algorithms based on templates mainly include Sum of Absolute Differences (SAD), Sum of Squared Differences (SSD), Normalized Cross Correlation (NCC), and Mutual Information (MI). In order to make it more reasonable to evaluate and compare the performance of the algorithms, in this paper, we decided to compare Mean Absolute Differences (MAD), Mean Square Differences (MSD), Zero-mean Normalized Cross Correlation (ZNCC), and Normalized Mutual Information (NMI). During the experiment, the Gaussian noise, illumination variations and occlusion were applied to the current image to simulate complex navigation scenes, and then matched it with the template images. The matching values obtained by the above four matching algorithms in different scenes were collectively called as alignment metric values. The matching effects of the four algorithms were evaluated from the following aspects including the smoothness of the metric value, the number of local extremums and whether the best position was in the correct alignment position. The results showed that the accuracy of MSD was greatly affected by noise and was not suitable for scenes interfered by noise, the number of local extremums of ZNCC changed greatly under the conditions of noise, illumination changes, and occlusion, the alignment metric values became unsmooth. In comparison, the NMI showed good robustness and accuracy in different conditions.

关键词： visual navigation template matching algorithm comparison mutual information global features

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Simple Improvement of Braitenberg Vehicles

International Core Journal of Engineering

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International Core Journal of Engineering 2021年第5期7卷 578-587页

作者： Jieyu Fan

Simple Improvement of the Braitenberg Vehicles, which aims at making the movements of simple car models more adaptive, is made by utilizing Object detector, which is a tool in Matlab to detect the position of the car and provides the position information for the algorithm to complete this process. In a word, to make the car turn by itself and based on the position information provided by Object detector in order to avoid all obstacles is the main goal of this project. Also, the comparison will be made among all the results from different versions of algorithms to finalize the algorithm, which is capable of making the car move in the fastest and most smooth ways while avoiding all obstacles. For further simulation of algorithm, my project will try to design more routes in more complex obstacles' environments--triangular routes with avoiding three obstacles.

关键词： Adaptive Object Detector Avoiding All Obstacles algorithm comparison Complex Environments

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AUV 3D Path Planning Based On A* algorithm

AUV 3D Path Planning Based On A* Algorithm

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Chinese Automation Congress (CAC)

作者： Li, Mengchuan Zhang, Huajun Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9781728176871

Aiming al the problem of global static path planning in the submarine terrain environment of autonomous underwater vehicle(AUV),A three-dimensional environment model was built based on gridmethod, and Dijsktra algorithm and A* algorithm were used to realize three-dimensional path search. The simulation results show that the search time of the two algorithms is shorter, hut the A* algorithm is better than Dijsktra algorithm in terms of the number of nodes and path length.A multi-direction A* algorithm is designed to reduce the number of search nodes and further shorten the search path. AUV 3d path planning has high efficiency and real-time performance.

关键词： A* algorithm Three-dimensional path planning algorithm comparison Node optimization

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Research on Image Feature Matching algorithm Applied to UAV Obstacle Avoidance

Research on Image Feature Matching Algorithm Applied to UAV ...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Zhu Haijie Li Jiafeng Cheng Sifan Qin Linlin Univ Sci & Technol China Dept Automat Hefei 230024 Peoples R China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158556

The ORB, SIFT, and SURF algorithms are currently common feature matching algorithms. These three algorithms have certain differences in execution speed and matching robustness. In this paper, the data sets provided by Mikolajczyk and Schmid are used to compare the algorithms in terms of execution speed, image transformation robustness, and noise robustness. The conclusion of this paper is that the ORB algorithm is the fastest, the SURF algorithm is the most robust, and the SIFT algorithm has the most feature points.

关键词： ORB SIFT SURF Feature Matching algorithm comparison

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The linear random forest algorithm and its advantages in machine learning assisted logging regression modeling

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2019年 174卷 776-789页

作者： Ao, Yile Li, Hongqi Zhu, Liping Ali, Sikandar Yang, Zhongguo China Univ Petr Beijing Peoples R China North China Univ Technol Beijing Peoples R China

Direct measurements of formation properties such as the shale volume, porosity, permeability, and fluid saturation are often accompanied by expensive cost and are time-consuming too. Well logging inversion provides an alternative way for the determination of formation properties. Compared to traditional theoretical models or formalized empirical fitted models, machine learning assisted logging regression modeling is more accurate and objective. Several machine learning regression algorithms such as neural networks, support vector regression, fuzzy logic, k nearest neighbors regression, multivariate adaptive regression spline, and random forest have already been applied. In this article, we present the Linear Random Forest algorithm and investigate its application in logging regression modeling. By systematic comparison with 8 other algorithms including least squared linear regression, neural networks, epsilon support vector regression, k nearest neighbors regression, regression tree, regression random forest, gradient descent boosted trees, and linear decision tree, the advantage of linear random forest in performance is confirmed by 24 real-world tasks from 7 different areas. Deeper discussions reveal that the advantages of linear random forest source from its strong learning ability, robustness, and feasibility of the hypothesis space. Through our study, the superiority of linear random forest for logging regression modeling is substantiated, which provides a more reasonable way for the further practices of logging regression modeling.

关键词： Machine learning Logging interpretation Logging regression modeling Linear random forest algorithm comparison

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Routing algorithm selection for field coverage planning based on field shape and fleet size

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2019年 156卷 523-529页

作者： Seyyedhasani, Hasan Dvorak, Joseph S. Roemmele, Eric Univ Calif Davis Biol & Agr Engn 2030 Bainer Hall Davis CA 95616 USA Univ Kentucky Biosyst & Agr Engn Dept 128 CE Barnhart Bldg Lexington KY 40546 USA Univ Kentucky Appl Stat Lab 323 Plant Sci Bldg Lexington KY 40546 USA

This project considered the field efficiency of routes created using two routing algorithms, a fast Clarke-Wright heuristic and a slower tabu search meta-heuristic, in 100 different field shapes with 1200 different field work scenarios for each algorithm. Different field work scenarios were generated by varying the number of simultaneously working vehicles (1, 2, 3, and 5) and using three path generation methods. After calculating the routes for all the scenarios using cloud computing and a high-performance compute cluster, the routes were evaluated to determine the field efficiency and field completion time. All tabu search results had field efficiencies above 0.65 and field completion times tightly clustered based on the number of simultaneously working vehicles. Many Clarke-Wright results were clustered with the tabu search results, but others had field efficiencies below 0.37 which indicated that the method failed to produce acceptable results. A logistic regression model was developed to identify the factors that caused unacceptable Clarke-Wright results. This enabled creation of a probability equation for predicting when the fast Clarke-Wright equation would produce acceptable results, and conversely, when it would be necessary to rely on the slower tabu search routing. Field shape complexity as measured by the isoperimetric quotient was the primary indicator that Clarke-Wright could fail to produce an acceptable result. The number of simultaneously operating vehicles was statistically insignificant for one, two or three vehicle fleets, but increasing to five vehicles did adversely affect the ability of the Clarke-Wright algorithm to provide acceptable routes.

关键词： Vehicle routing problem Tabu search Clarke-wright algorithm comparison Agricultural machinery

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Multi-objective ligand-protein docking with particle swarm optimizers

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SWARM AND EVOLUTIONARY COMPUTATION 2019年 44卷 439-452页

作者： Garcia-Nieto, Jose Lopez-Camacho, Esteban Jesus Garcia-Godoy, Maria Nebro, Antonio J. Aldana-Montes, Jose F. Univ Malaga ETSI Informat Dept Lenguajes & Ciencias Computac Campus Teatinos E-29071 Malaga Spain

In the last years, particle swarm optimizers have emerged as prominent search methods to solve the molecular docking problem. A new approach to address this problem consists in a multi-objective formulation, minimizing the intermolecular energy and the Root Mean Square Deviation (RMSD) between the atom coordinates of the co-crystallized and the predicted ligand conformations. In this paper, we analyze the performance of a set of multi-objective particle swarm optimization variants based on different archiving and leader selection strategies, in the scope of molecular docking. The conducted experiments involve a large set of 75 molecular instances from the Protein Data Bank database (PDB) characterized by different sizes of HIV-protease inhibitors. The main motivation is to provide molecular biologists with unbiased conclusions concerning which algorithmic variant should be used in drug discovery. Our study confirms that the multi-objective particle swarm algorithms SMPSOhv and MPSO/D show the best overall performance. An analysis of the resulting molecular ligand conformations, in terms of binding site and molecular interactions, is also performed to validate the solutions found, from a biological point of view.

关键词： Multi-objective optimization Particle swarm optimization Molecular docking Archiving strategies algorithm comparison

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New Criteria for Comparing Global Stochastic Derivative-Free Optimization algorithms

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2019年第7期10卷 614-625页

作者： McCart, Jonathan Almomani, Ahmad SUNY Coll Geneseo Dept Math Geneseo NY 14454 USA

For many situations, the function that best models a situation or data set can have a derivative that may be difficult or impossible to find, leading to difficulties in obtaining information about the optimal values of the function. Thus, numerical methods for finding these important values without the direct involvement of the derivative have been developed, making the representation and interpretation of the results for these algorithms of importance to the researchers using them. This is the motivation to use and compare between derivative-free optimization (DFO) algorithms. The comparison methods developed in this paper were tested using three global solvers: Genetic algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA) on a set of 26 n-dimensional test problems of varying convexity, continuity, differentiability, separability, and modality. Each solver was run 100 times per problem at 2, 20, 50 and 100 dimensions. The formulation for each algorithm used comes from the MATLAB Optimization Toolbox, unedited or revised. New criteria for comparing DFO solver performance are introduced in terms defined as Speed, Accuracy, and Efficiency, taken at different levels of precision and dimensionality. The numerical results for these benchmark problems are analyzed using these methods.

关键词： Derivative-free optimization algorithm comparison test problem benchmarking

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comparison of advantages and disadvantages among various algorithms in logistics path-design Taking H-group as an example

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COGNITIVE SYSTEMS RESEARCH 2018年 52卷 843-852页

作者： Yu, Miao Li, Shuo Kong, Menglei Song, Jinguo Yang, Jing Ren, Guowen China Univ Polit Sci & Law Business Sch Beijing Peoples R China North China Elect Power Univ Sch Econ & Management Beijing Peoples R China

There are many kinds of VRP problems and there are many ways to solve them. In this paper, we use ant colony algorithm, genetic algorithm, and annealing algorithm to optimize the selection of the logistics path of H-group located at He Nan Province. It establishes an algorithm evaluation system, and analyzes the performance of the three algorithms in six dimensions from qualitative and quantitative perspectives. Through MATLAB data calculation, we found that the ant colony algorithm performs equally well on the solution quality, solution efficiency, code storage, robustness, adaptability, and optimality. (C) 2018 Published by Elsevier B.V.

关键词： VRP Various algorithms algorithm comparison

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Development of a Web Based Framework to Objectively Compare and Evaluate Software Solutions

Development of a Web Based Framework to Objectively Compare ...

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9th Int Conf on Appl Human Factors and Ergon (AHFE) / Int Conf on Human Factors, Software, and Syst Engn, Artificial Intelligence and Social Comp, Human Side of Serv Engn and Human Factors in Energy (HSSE)

作者： Barta, Maximilian Schimanski, Sigmund Buchhorn, Julian Nawrot, Adalbert Berg Univ Wuppertal Human Factors Engn Rainer Gruenter Str 21 D-42119 Wuppertal Germany

ISBN: (纸本)9783319942292;9783319942285

We created a web based framework to objectively evaluate different software solutions using different approaches to the same problem. Solutions can either be single algorithms, software modules or entire programs. The evaluation strongly relies on the human component. In this paper we describe the conceptual structure as well as the evaluation of the first field test of the developed framework by utilizing the implementation of two distinct georouting algorithms as well as their validation with test users. No modification to the tested software needs to be done, as the state of each software component is saved and synchronized by the framework. The aim of the investigation of our implementation is to gather usage data, which then allows us to derive proposals for improvements upon the area of usability and user experience and to identify properties that increases the productivity of users as well as finding out about bottlenecks. The framework is validated by assessing the collected metrics and the user feedback produced by the test, as distinctions in usage, user experience and usability between the two test algorithms were identified.

关键词： algorithm comparison Evaluation framework Human factors engineering Systems engineering User centered Web technologies

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