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检索条件"任意字段=5th International Conference on Fun with Algorithms"

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5th international conference on Optimization and Learning, OLA 2022

5th International Conference on Optimization and Learning, O...

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5th international conference on Optimization and Learning, OLA 2022

ISBN: (纸本)9783031220388

the proceedings contain 19 papers. the special focus in this conference is on Optimization and Learning. the topics include: Sweep algorithms for the Vehicle Routing Problem with Time Windows;improving the Accuracy of Vehicle Routing Problem Approximation Using the Formula for the Average Distance Between a Point and a Rectangular Area;optimal Delivery Area Assignment for the Capital Vehicle Routing Problem Based on a Maximum Likelihood Approach;neural Order-First Split-Second Algorithm for the Capacitated Vehicle Routing Problem;GRASP-Based Hybrid Search to Solve the Multi-objective Requirements Selection Problem;Comparing Parallel Surrogate-Based and Surrogate-Free Multi-objective Optimization of COVID-19 Vaccines Allocation;decentralizing and Optimizing Nation-Wide Employee Allocation While Simultaneously Maximizing Employee Satisfaction;categorical-Continuous Bayesian Optimization Applied to Chemical Reactions;assessing Similarity-Based Grammar-Guided Genetic Programming Approaches for Program Synthesis;maximum Information Coverage and Monitoring Path Planning with Unmanned Surface Vehicles Using Deep Reinforcement Learning;tuning ForestDisc Hyperparameters: A Sensitivity Analysis;multi-objective Hyperparameter Optimization with Performance Uncertainty;a New Algorithm for Bi-objective Problems Based on Gradient Information;adaptive Continuous Multi-objective Optimization Using Cooperative Agents;integer Linear Programming Reformulations for the Linear Ordering Problem;SHAMan: A Versatile Auto-tuning Framework for Costly and Noisy HPC Systems;cooperation-Based Search of Global Optima.

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Particle Swarm Optimization and Genetic algorithms for PID Controller Tuning

Particle Swarm Optimization and Genetic Algorithms for PID C...

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international conference on Smart Systems and Inventive Technology (ICSSIT)

作者： Debani Prasad Mishra Usharani Raut Anubhav Prakash Gaur Sriram Swain Suraj Chauhan Electrical and Electronics(EEE) International Institute of Information Technology Bhubaneswar Bhubaneswar India

this article compares the tuning of an inverted pendulum’s proportional-integral-derivative (PID) parameters using heuristic approaches. this study intends to develop an inverted pendulum model with parameters that are based on real-world conditions. the adjustment of the pendulum’s PID parameters is subsequently turned into an optimization issue. Particle swarm optimization. genetic algorithms. and a mix of the two are used to overcome this issue. After simulation in the Simulink and MATLAB environments, the success of the suggested PID tuning procedures is finally confirmed by performance indices. To get the most out of the article time response analysis is done using parameters such as max. overshoot, settling time, peak time, etc.

关键词： Costs Sociology Time factors PD control Particle swarm optimization Statistics Tuning

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A Novel Roof Detection Algorithm Based SLSC Supervoxel for Airborne LiDAR Point Cloud Data

A Novel Roof Detection Algorithm Based SLSC Supervoxel for A...

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Power Electronics, Computer Applications (ICPECA), IEEE international conference on

作者： Lili Yue Mengqing Yun Di Han School of Marxism Jilin Communications Polytechnic Changchun China Cloud Computing Center China Telecom Chengdu China International Education Jilin Communications Polytechnic Changchun China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

A new roof detection framework is proposed in this article for detecting roofs from raw point cloud obtained from ALS (Airborne Laser Scanner). there are two main problems solved by the framework, the first problem is that the traditional supervoxel-based algorithm cannot provide accurate feature extraction regions, leading to degradation of classification performance. the second problem is that traditional individual roof segmentation algorithms suffer from the difficulty of ensuring a balance between efficiency and accuracy. To address the first problem, a SLSC (Supervoxel-based Linear Spectral Clustering Segmentation) algorithm is proposed for the feature extraction, which takes into account the correlation of local neighbor changes in terms of supervoxels and provides suitable neighbors for feature computation. Experiments are conducted on two ALS point cloud datasets to evaluate the performance of the algorithms in this article. this algorithm achieved advanced results on two datasets, with overall accuracies of 73.29% and 81.21%, respectively.

关键词： Point cloud compression Accuracy Buildings Lasers Clustering algorithms Feature extraction Power electronics Classification algorithms Detection algorithms Random forests

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On the Development of international Environmental Law from the Perspective of international Relations theory Under Genetic Algorithm 5th

On the Development of International Environmental Law from t...

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5th international conference on Innovative Computing, IC 2022

作者： Shi, Jiahui Hankou University Hubei Wuhan430212 China

ISBN: (纸本)9789811941313

the adjustment object of international environmental law is international environmental relations, so the relationship between international environmental law and international relations theory is very close. the theory of international mechanism of Neo liberalism promotes the emergence of international environmental law, the theory of international relations of Constructivism accelerates the development of international environmental law, and the theory of international relations of community of human destiny will lead the future development of international environmental law. international relations theory reveals the theoretical roots of the emergence and development of international environmental law to a certain extent. this paper analyzes the development of international environmental law from the perspective of international relations theory under genetic algorithm, and forecasts the future development prospects of international environmental law. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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Research on kiwifruit grading detection system based on depth limit learning machine 5

Research on kiwifruit grading detection system based on dept...

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5th international conference on algorithms, Computing and Artificial Intelligence, ACAI 2022

作者： Wang, Liang Department of Engineering Management International College Krirk University Bangkok10220 Thailand

ISBN: (纸本)9781450398343

Aiming at the low recognition rate and low accuracy of traditional kiwifruit grading detection, a feature extraction method based on machine vision kiwifruit detection system is proposed. In order to improve the recognition accuracy, the R component map is used as the input map, and the median filtering method is used to denoise and extract the surface defect features of kiwifruit. On this basis, the least square method is used to establish the ellipse fitting curve to extract the size features, and the mean and standard deviation of H, I, S are used to extract the color features;At the same time, 30 models were selected to establish the deep extreme learning machine (DELM) model to identify kiwifruit defects. Finally, 326 kiwi images were constructed, and the results showed that the correct recognition rate of the depth limit learning machine model was 97.5%, which could achieve accurate grading. © 2022 ACM.

关键词： Feature extraction

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Classification of ECG based on Hybrid Features using CNNs for Wearable Applications 5

Classification of ECG based on Hybrid Features using CNNs fo...

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5th IEEE international conference on Artificial Intelligence Circuits and Systems, AICAS 2023

作者： Xiaolin, Li Xiang, Fang Panicker, Rajesh C. Cardiff, Barry John, Deepu University College Dublin Ireland Beijing-Dublin International College Iran National University of Singapore Singapore

ISBN: (纸本)9798350332674

Sudden cardiac death and arrhythmia account for a large percentage of all deaths worldwide. Electrocardiography (ECG) is the most widely used screening tool for cardiovascular diseases. Traditionally, ECG signals are classified manually, requiring experience and great skill, while being time-consuming and prone to error. thus machine learning algorithms have been widely adopted because of their ability to perform complex data analysis. Features derived from the points of interest in ECG - mainly Q, R, and S, are widely used for arrhythmia detection. In this work, we demonstrate improved performance for ECG classification using hybrid features and three different models, building on a 1-D convolutional neural network (CNN) model that we had proposed in the past. An RR interval features based model proposed in this work achieved an accuracy of 98.98%, which is an improvement over the baseline model. To make the model immune to noise, we updated the model using frequency features and achieved good sustained performance in presence of noise with a slightly lower accuracy of 98.69%. Further, another model combining the frequency features and the RR interval features was developed, which achieved a high accuracy of 99% with good sustained performance in noisy environments. Due to its high accuracy and noise immunity, the proposed model which combines multiple hybrid features is well suited for ambulatory wearable sensing applications. © 2023 IEEE.

关键词： Electrocardiography

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A Masked Facial Landmarks Localization Method Considering the Mask-Face Contact Characteristics 22

A Masked Facial Landmarks Localization Method Considering th...

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5th international conference on Data Storage and Data Engineering, DSDE 2022

作者： Chen, Yiwen Zhu, Lingyun Liangjiang International College Chongqing University of Technology China

ISBN: (纸本)9781450395724

At present, it has become normal for people to travel with masks. In order to meet the challenge of face recognition caused by mask occlusion, a new method for landmark localization of masked face was proposed in this study. Correspondingly, a 68-point shape model including face and mask was designed and the distribution of the related landmarks was pre-positioned according to the fitting characteristics between the face and mask. To generate a regressor with function of accurate localization of facial landmarks, the masked face dataset marked by the shape model was constructed;Meanwhile, the regression tree integration algorithm was used to accurately locate the pre-positioned landmarks of the masked face. By means of the method established in this study, the tested value of IPN and ION is respectively equal to 5.68 and 3.65, being less than those of other classical algorithms. the experimental results indicate that this method can achieve an acceptable landmark localization effect and is likely to provide certain technical supports for the masked face recognition. © 2022 ACM.

关键词： Face recognition

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Energy Aware Scheduling and Resource Allocation for Virtual Machine

Energy Aware Scheduling and Resource Allocation for Virtual ...

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Sustainable Technologies for Industry 4.0 (STI), international conference on

作者： Md Mehefujur Rahman Mubin Sajjad Ullah James Anthony Purification Md. Motaharul Islam Department of Computer Science and Engineering United International University Dhaka Bangladesh

With the growing demand for high-performance computing on virtual machines and cloud servers, which consume more power to deliver optimal performance, the need for energy-aware scheduling and resource allocation of virtual machines has become crucial. this research investigates the impact and effectiveness of energy-aware scheduling in optimizing energy consumption and resource utilization. To improve energy efficiency and optimize the consumption of virtual machines, several strategies have been employed. these include allocating clients using different scheduling algorithms based on the workload status of the VMs, as well as implementing Live Migration along with algorithms to enhance network efficiency. these algorithms are established based on process scheduling algorithms used in operating systems, ensuring users experience seamless performance on virtual machines and cloud services. Perfor-mance metrics, including response time, throughput, and average turnaround time are measured in this research to evaluate the different approaches. the experimental results demonstrate the efficacy of the proposed techniques, which achieved significant energy savings compared to existing algorithms. We observed a 0.09% improvement in overall turnaround time compared to the static scheduling algorithm and a 9.96% improvement in overall throughput through our dynamic scheduling algorithm. these findings highlight the potential of energy-aware algorithms and techniques in optimizing energy consumption and improving resource utilization in virtual machine environments.

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Development of a Simulation Environment for Robot Soccer Game with Deep Reinforcement Learning and Role Assignment 5

Development of a Simulation Environment for Robot Soccer Gam...

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5th World Robot conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhong, Hanzhong Zhu, Haier Li, Xiang Tsinghua University Department of Automation China Tsinghua University Tsinghua Shenzhen International Graduate School China

ISBN: (纸本)9798350307320

the robot soccer game has been recognized as an excellent scenario to test the gaming algorithm of multi-agent systems. this paper develops a new simulation platform for the robot soccer game, and it has the advantage of open architecture, such that the formation control scheme, the path planning strategy for multiple robots, and many other algorithms can be implemented and tested. Specifically, both a Deep Reinforcement Learning (DRL) scheme and a role-assignment-based method have been successfully realized in this platform to drive multiple robots to play the soccer game, including 2V2,3V3,4V4, and so on. It is believed that the developed simulation environment can be used for data collection and transfer learning (TL), hence bridging the gap of Sim2Real technique in actual implementations. © 2023 IEEE.

关键词： Reinforcement learning

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5th international conference on Smart Computing and Informatics, SCI 2021

5th International Conference on Smart Computing and Informat...

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5th international conference on Smart Computing and Informatics, SCI 2021

ISBN: (纸本)9789811697043

the proceedings contain 58 papers. the special focus in this conference is on Smart Computing and Informatics. the topics include: QCA-Based Error Detection Circuit for Nanocommunication Network;evaluating Performance on Covid-19 Tweet Sentiment Analysis Outbreak Using Support Vector Machine;minimum Simplex Nonlinear Nonnegative Matrix Factorization for Hyperspectral Unmixing;prediction and Analysis of Vitamin D Deficiency Using Machine Learning algorithms;student Performance Prediction Using Classification Models;estimating Driver Attentiveness through Head Pose Using Hybrid Geometric-Based Method;IIWSCOA-Based DCNN: Improved Invasive Weed Sine Cosine Optimization Algorithm for Early Detection of Myocardial Infarction Using Deep Convolution Neural Network;intrusion Detection Using Support Vector Machine and Artificial Neural Network;student’s Academic Performance Prediction Using Ensemble Methods through Educational Data Mining;A Flexible Accession on Brain Tumour Detection and Classification Using VGG16 Model;check Certificate—A Certificate Verification Platform for Students and Organizations;secure Cluster-Based Routing Using Modified Spider Monkey Optimization for Wireless Sensor Networks;ChefAI Text to Instructional Visualization Using Amazon Web Services;Identification of Predominant Genes that Causes Autism Using MLP;Detecting Impersonators in Examination Halls Using AI;telugu Text Classification Using Supervised Machine Learning Algorithm;Application of Hybrid MLP-GWO for Monthly Rainfall Forecasting in Cachar, Assam: A Case Study;Temperature Prediction Using Hybrid MLP-GOA Algorithm in Keonjhar, Odisha: A Case Study;development of Different Word Vectors and Testing Using Text Classification algorithms for Telugu;addressing Longtail Problem using Adaptive Clustering for Music Recommendation System;A Proficient GK-KMA Based Segmentation and Lung Nodule Detection in CT Images Using PTRNN;framework for Diabetic Retinopathy Classification.

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