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Development and Experimental Research of Data analysis algorithm of Animal's Daily Activities in Automated Information Management System for Livestock Enterprises

Development and Experimental Research of Data Analysis Algor...

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International Conference on Stability and Control Processes in Memory of V.I. Zubov (SCP)

作者： Antonov, Lev Privezentsev, Denis Orlov, Alexey Vladimir State Univ Dept Phys & Appl Math Murom Inst Branch Murom Russia Vladimir State Univ Dept Syst Comp Aided Design Murom Inst Branch Murom Russia

ISBN: (纸本)9781467376983

The task of identifying critical fluctuations of the production characteristics from the normal value are considered in the article. An algorithm based on the least squares method, which allows for an increase of efficiency and accuracy in identifying problematic situations in production is developed in the course of research. Experimental research of the developed algorithm was performed using four different metrics.

关键词： Management Information Systems livestock enterprises analysis of algorithm Normal Range Daily Activities critical fluctuations

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Demystifying Complex algorithms: A Visual Guide Through the DSA Visualizer 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Matalia, Jeet Kathiriand, Shreya Patel, Priyanka Charotar Univ Sci & Technol CHARUSAT Chandubhai S Patel Inst Technol Fac Engn & Technol Smt Kundaben Dinsha Patel Dept Informat Technol Changa 388421 Gujarat India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

The foundation of computer science is made up of data structures and algorithms (DSA), which are necessary for creating effective software solutions and resolving challenging issues. But learning the nuances of DSAs can be difficult and frequently poses a big barrier to entry for both programmers and students. DSA Visualizers have become indispensable resources for improving the acquisition and comprehension of these important ideas in response to this challenge. This paper focuses on the visualization of data structures and algorithms. A web application has been developed to help students understand step-by-step working of different data structures and algorithms. Aim behind implementation of this paper is to make a clear understandability of various algorithms of data structures. This web app will simulate the data structure operations such as searching and sorting. In array, stack, queue, and linked list as well. Data structure and algorithm learning has been made easier thanks in large part to DSA Visualizers. Their visual and interactive method breaks down difficult ideas into easily understood models, allowing students to become more proficient in problem-solving and programming. DSA Visualizers are invaluable resources that help people of all skill levels, from beginners to experts in programming, understand DSAs, and make it easier to use them in real-world computer science applications.

关键词： Data structure and algorithm analysis of algorithm Complexity and applications Visual representation Searching and sorting algorithm algorithm design

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Convergence analysis of standard particle swarm optimization algorithm and its improvement

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SOFT COMPUTING 2018年第12期22卷 4047-4070页

作者： Qian, Weiyi Li, Ming Bohai Univ Coll Math & Phys Jinzhou 121000 Peoples R China

Standard particle swarm optimization (PSO) algorithm is a kind of stochastic optimization algorithm. Its convergence, based on probability theory, is analyzed in detail. We prove that the standard PSO algorithm is convergence with probability 1 under certain condition. Then, a new improved particle swarm optimization (IPSO) algorithm is proposed to ensure that IPSO algorithm is convergence with probability 1. In order to balance the exploration and exploitation abilities of IPSO algorithm, we propose the exploration and exploitation operators and weight the two operators in IPSO algorithm. Finally, IPSO algorithm is tested on 13 benchmark test functions and compared with the other algorithms published in the recent literature. The numerical results confirm that IPSO algorithm has the better performance in solving nonlinear functions.

关键词： Standard particle swarm optimization analysis of algorithm Convergence in probability Global optimization

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The analysis of evolutionary optimisation on the TSP(1,2) problem

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2019年第3期18卷 261-268页

作者： Xia, Xiaoyun Lai, Xinsheng Yi, Chenfu Jiaxing Univ Coll Math Phys & Informat Engn Jiaxing 314001 Zhejiang Peoples R China Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China Shangrao Normal Univ Sch Math & Comp Sci Shangrao 334001 Peoples R China

TSP(1,2) problem is a special case of the travelling salesperson problem which is NP-hard. Many heuristics including evolutionary algorithms (EAs) are proposed to solve the TSP(1,2) problem. However, we know little about the performance of the EAs for the TSP(1,2) problem. This paper presents an approximation analysis of the (1+1) EA on this problem. It is shown that both the (1+1) EA and (mu+lambda) EA can obtain 3/2 approximation ratio for this problem in expected polynomial runtime O(n(3)) and O ((mu/lambda)n(3) + n), respectively. Furthermore, we prove that the (1+1) EA can provide a much tighter upper bound than a simple ACO on the TSP(1,2) problem.

关键词： evolutionary algorithms TSP(1,2) approximation performance analysis of algorithm computational complexity

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Comparative analysis of algorithms for processing inconsistent data on the example of comparisons CCQM-K131

Comparative analysis of algorithms for processing inconsiste...

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International Scientific Symposium on Metrology and Metrology Assurance (MMA)

作者： Burmistrova Natalia Viktorov Ivan Chunovkina Anna D.I. Mendeleev Institute for Metrology (VNIIM) St. Petersburg Russia

The paper given contains a discussion of the methodology for evaluating the inconsistent data of comparisons. The most widely used approaches are taken into account. As well a detailed comparative analysis of two algo... 详细信息

ISBN: (纸本)9781728122144

关键词： Inconsistent data Metrological compatibility Uncertain ty Reference value Degree of equivalence inconsistent data reference value analysis of algorithm algorithms

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A Novel algorithm for analysis of a Local Shape In the 3-D Gray Image

A Novel Algorithm for Analysis of a Local Shape In the 3-D G...

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Global Conference for Advancement in Technology (GCAT)

作者： Srinivasa Rao Perumalla Yedukondalu Kamtham Department of Electronicsa & Communication Enginnering CVR College of Engineering Hyderabad India

ISBN: (纸本)9781728136950

For shape analysis in 3-D, probably skeletonization will become a momentous tool for analyzing the different shapes in 3-D, as similar to the 2-D. This paper discusses about topology preserving 3-D skeletonization sequential algorithm which computes curve skeletons for the given solid object. The original geometry of the given object will be well-preserved by curve skeleton. In the proposed algorithm, each voxel of the three-dimensional image is classified as two classes: boundary, corner. The object is scanned with the use of a structuring element, border and corner voxels are classified based on the certain condition proposed in this paper. This algorithm does not require any computations which are complex, large number of windows which make implementation a complex. The proposed algorithm is various 3-D simulated images and resulting skeletons are found to satisfactory. The 3-D simulated images and its skeletons are viewed with the help of ImageJ software.

关键词： curve fitting image classification image colour analysis shape recognition image colour analysis shape recognition Curve fitting Image classification Skeletons analysis of algorithm Pattern recognition Three Dimensions grayscale images Three-Dimensional Images analog image SKELETONIZATION

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MAPFAST: A Deep algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings 21

MAPFAST: A Deep Algorithm Selector for Multi Agent Path Find...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Jingyao Ren Vikraman Sathiyanarayanan Eric Ewing Baskin Senbaslar Nora Ayanian University of Southern California

ISBN: (纸本)9781713832621

Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to be NP-Hard for both make-span and total arrival time minimization. While many algorithms have been developed to solve MAPF problems, there is no dominating optimal MAPF algorithm that works well in all types of problems and no standard guidelines for when to use which algorithm. In this work, we develop the deep convolutional network MAPFAST (Multi-Agent Path Finding algorithm SelecTor), which takes a MAPF problem instance and attempts to select the fastest algorithm to use from a portfolio of algorithms. We improve the performance of our model by including single-agent shortest paths in the instance embedding given to our model and by utilizing supplemental loss functions in addition to a classification loss. We evaluate our model on a large and diverse dataset of MAPF instances, showing that it outperforms all individual algorithms in its portfolio as well as the state-of-the-art optimal MAPF algorithm selector. We also provide an analysis of algorithm behavior in our dataset to gain a deeper understanding of optimal MAPF algorithms' strengths and weaknesses to help other researchers leverage different heuristics in algorithm designs.

关键词： Multi-Agent path finding algorithm selection Deep learning algorithms selectors Dataset Nondeterministic polynomial-time hard shortest path FINDINGS BRIEFCASE Byways analysis of algorithm

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A High-Voltage Circuit Breaker Condition Assessment Method using the Vibration Fingerprint based on VMD-EM method

A High-Voltage Circuit Breaker Condition Assessment Method u...

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IEEE Instrumentation and Measurement Technology Conference

作者： Kerim Obarcanin Bakir Lacevic Michele Ermidoro DV Power Stockholm Sweden Faculty of Electrical Engineering Sarajevo Bosnia and Herzegovina University of Bergamo Bergamo Italy

ISBN: (数字)9781728144603

ISBN: (纸本)9781728144610

The reliability of the operations of the high-voltage circuit breaker is the key to the stable power system, so it's fault diagnosis and condition assessment it is of great significance. Considering that high-voltage circuit breaker vibration fingerprints contain valuable information about its mechanical integrity and that the vibration measurements are non-invasive, this paper presents the algorithm for the analysis of residual life of a high-voltage circuit breaker. The algorithm is based on the variational mode decomposition (VMD) and Shannon information entropy mean (EM) in order to obtain indices that are used as an indicator of the circuit breaker structural deterioration.

关键词： high-voltage circuit breaker vibration analysis variational mode decomposition high voltage circuit breakers Vibration analysis Condition assessment vibration monitoring analysis of algorithm residual life circuit breakers

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On Weighted Depths in Random Binary Search Trees

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JOURNAL OF THEORETICAL PROBABILITY 2018年第4期31卷 1929-1951页

作者： Aguech, Rafik Amri, Anis Sulzbach, Henning King Saud Univ Coll Sci Dept Stat & Operat Res POB 2455 Riyadh 11451 Saudi Arabia Univ Monastir Ave Taher HaddedBP 56 Monastir 5000 Tunisia Univ Birmingham Sch Math Birmingham B15 2TT W Midlands England

Following the model introduced by Aguech et al. (Probab Eng Inf Sci 21:133-141, 2007), the weighted depth of a node in a labelled rooted tree is the sum of all labels on the path connecting the node to the root. We analyse weighted depths of nodes with given labels, the last inserted node, nodes ordered as visited by the depth first search process, the weighted path length and the weighted Wiener index in a random binary search tree. We establish three regimes of nodes depending on whether the second-order behaviour of their weighted depths follows from fluctuations of the keys on the path, the depth of the nodes or both. Finally, we investigate a random distribution function on the unit interval arising as scaling limit for weighted depths of nodes with at most one child.

关键词： analysis of algorithm Data structures Binary search trees Central limit theorems Contraction method Random probability measures

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A brief survey on deep learning based methods for lung cancer classification using computerized tomography scans

A brief survey on deep learning based methods for lung cance...

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CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

作者： Mario G. Borja Borja Roger Huauya Cristian Lazo Department of Mechanical Engineering Universidad Nacional de Ingeniería Lima Lima Peru

ISBN: (纸本)9781728131863

In this paper, we present a brief but critic survey of deep learning approaches in solving the remarkable task of lung cancer detection using computerized tomography scans. This is a survey paper that is intended to give the reader the cuttingedge algorithms to solve this task. We reviewed over 20 papers related to this topic to cover the best methods to approach this problem. In addition, our work develops a review not only in the algorithm, but also in the input dataset, the computerized tomography scans. At the end, we conclude with a summary of the current state-of-the-art methods, an overall analysis of the algorithms revised and some considerations to solve the lung cancer classification task in computerized tomography.

关键词： cancer computerised tomography learning (artificial intelligence) lung medical image processing pattern classification X-Ray Computed Tomography Medical image processing Pattern recognition Lung Lung Cancer algorithms analysis of algorithm cancer classification

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