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检索条件"任意字段=7th International Conference on Algorithms and Complexity"

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A Study on the Interpretability of Collegiate Panel Judgment Prediction Based on Concept Tree XGBoost

A Study on the Interpretability of Collegiate Panel Judgment...

引用

Data Science and Information Technology (DSIT), international conference on

作者： JiaYu Liu School of Foreign Language and Literature School of Law Wuhan University Wuhan

ISBN: (数字)9798350384093

ISBN: (纸本)9798350384109

Currently, the majority of artificial intelligence algorithms and models employed by the Institute of Computational Law exhibit "black box" characteristics and insufficient interpretability. this field is in urgent need of models that possess both high performance and high interpretability. therefore, this paper focuses on the prediction of collegiate panel judgments, utilizing the Concept Tree XGBoost algorithm to construct a prediction model. Furthermore, the SHAP interpretation method is integrated into this model to quantify and attribute the judgment outcomes. the experimental results demonstrate that this model can achieve favorable prediction outcomes and, to a certain extent, meet the interpretability requirements of collegiate panel judgment models in practical applications.

关键词： Training Computational modeling Predictive models Data science Prediction algorithms Data models complexity theory Classification algorithms Information technology Artificial intelligence

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Proceedings - 7th international conference on Computer Science and Engineering, UBMK 2022

Proceedings - 7th International Conference on Computer Scien...

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7th international conference on Computer Science and Engineering, UBMK 2022

ISBN: (纸本)9781665470100

the proceedings contain 98 papers. the topics discussed include: linguistic-based data augmentation approach for offensive language detection;a mixed reality interface for tactical data management in geographic information systems;the effect of statistical attributes on the determination of stock trading actions;reverse ant colony optimization for the winner determination problem in combinatorial auctions;brain computer interaction and cybersecurity of the brain;an anomaly detection study for the smart home environment;what does industry suggest to academia on software engineering education?;anomaly pattern analysis based on machine learning on real telecommunication data;explainable ai for software defect prediction with gradient boosting classifier;data augmentation of morphological brain network using multi-variate normal distribution;applying web crawler technologies for compiling parallel corpora as one stage of natural language processing;comparison of heuristic and metaheuristic algorithms;and a new algorithm for the initial feasible solutions of fixed charge transportation problem.

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A Solution to User Fairness in NOMA Heterogeneous Networks Based on Channel Selection and Power Optimization 7th

A Solution to User Fairness in NOMA Heterogeneous Networks B...

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7th international conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Zhang, Dongpo Chen, Chunlei Wang, Zhaorong An, Xiujuan The 36th Research Institute of China Electronic Technology Corporation Zhejiang Jiaxing China Department of Electronic and Communication Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9789819624089

In the optimization process aimed at maximizing the overall transmission rate in 5G heterogeneous non-orthogonal multiple access networks, the issue of unequal resource allocation arises. this phenomenon directly results in significantly lower minimum rates for channels with poor transmission conditions. Under such circumstances, the service quality of affected users suffers negative impacts, leading to unbalanced service experiences among users. To address this issue, this paper proposes a strategy that decouples the overall optimization problem and combines optimal channel pairing selection with user power allocation optimization to ensure the maximization of the minimum user rate and address fairness issues among users. Firstly, this paper elaborates on the decoupling method for the overall optimization problem. Subsequently, it details the implementation of optimal user pairing selection and user power allocation optimization. Simulation verifications are conducted using system parameters that closely resemble actual scenarios. the simulation results demonstrate that the algorithm proposed in this paper significantly improves the minimum user rate without increasing system complexity, effectively addressing fairness issues among users to a certain extent. © the Author(s) 2025.

关键词： 5G mobile communication systems

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A Beamspace-Based Orthogonal Matching Pursuit DOA Estimation Algorithm

A Beamspace-Based Orthogonal Matching Pursuit DOA Estimation...

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IEEE international conference on Information Communication and Signal Processing (ICICSP)

作者： Zhongchuan Sun Shuo Wang Kexin Jia Shuaishuai Pan East China Electronic Engineering Institute Hefei China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

In order to solve the problem that the traditional Direction of Arrival (DOA) estimation algorithm is seriously affected by the multipath effect and has high computational complexity when tracking at low elevation angles, this study innovatively proposes an Orthogonal Matching Pursuit (OMP) algorithm based on beam space. this algorithm first performs multibeam coverage of the target, maps the received signal from the array element domain to the beam domain, and then utilizes the theory of compressed perception to compressively sample the airspace signals in the beam space, so as to efficiently extract the data information. Compared with the traditional DOA estimation algorithms, such as the Capon Beamforming (CAPON) algorithm and the Multiple Signal Classification (MUSIC) algorithm, the algorithm proposed in this paper has stronger resistance to multipath interference. Compared with the array-element level OMP algorithm and the L 1 -Norm Singular Value Decomposition (L 1 -SVD) algorithm, the algorithm computation is significantly reduced and the real-time tracking capability of the system is improved.

关键词： Direction-of-arrival estimation Accuracy Matching pursuit algorithms Signal processing algorithms Estimation Interference Real-time systems Classification algorithms Arrays Computational complexity

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Bipartite Domination in Graphs: complexity and algorithms 11th

Bipartite Domination in Graphs: Complexity and Algorithms

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11th international conference on algorithms and Discrete Applied Mathematics, CALDAM 2025

作者： Panda, Bhawani Sankar Joshi, Subhasmita Jacob, Dalu Department of Computer Science and Engineering The LNM Institute of Information Technology Jaipur302031 India Department of Mathematics Indian Institute of Technology Delhi Hauz Khas New Delhi110016 India

ISBN: (纸本)9783031834370

A set D⊆V of vertices of a graph G=(V,E) is called a dominating set of G if for every vertex u∈V\D, there exists a vertex v∈D such that uv∈E(G). A dominating set D is called a bipartite dominating set if G[D], the subgraph induced by D, is bipartite. the domination number of G is the minimum cardinality among all dominating sets of G and it is denoted by γ(G). the bipartite domination number of G is the minimum cardinality among all bipartite dominating sets of G and it is denoted by γbip(G). the Min Dom problem is to find a dominating set of minimum cardinality of a given graph G and Decide Dom is the decision version of the Min Dom problem. Similarly, the Min Bip-Dom problem is to find a bipartite dominating set of minimum cardinality of a given graph G and Decide Bip-Dom is the decision version of the Min Bip-Dom problem. In this paper, we initiate the algorithmic study of the Min Bip-Dom problem. First, we study the complexity difference between the Min Dom problem and the Min Bip-Dom problem. the difference between γbip(G) and γ(G) of a graph G can be arbitrarily large. However, the Decide Bip-Dom problem is the same as the Decide Dom problem for bipartite graphs and hence is NP-complete for bipartite graphs, as Decide Dom problem is known to be NP-complete for bipartite graphs. We show that Decide Bip-Dom is NP-complete for non-bipartite graphs as well. Finally, we propose polynomial-time algorithms for the Min Bip-Dom problem for interval graphs and block graphs. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Consensus algorithm

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A New Highly Efficient Preprocessing Algorithm for Convex Hull, Maximum Distance and Minimal Bounding Circle in E²: Efficiency Analysis 24th

A New Highly Efficient Preprocessing Algorithm for Convex Hu...

引用

24th international conference on Computational Science (ICCS)

作者： Skala, Vaclav Univ West Bohemia Fac Appl Sci Dept Comp Sci & Engn CZ-30100 Plzen Czech Republic

ISBN: (纸本)9783031637582;9783031637599

this contribution describes an efficient and simple preprocessing algorithm for finding a convex hull, maximum distance of points or convex hull diameter, and the smallest enclosing circle in E-2. the proposed algorithm is convenient for large data sets with unknown intervals and ranges of the data sets. It is based on efficient preprocessing, which significantly reduces points used in final processing by standard available algorithms.

关键词： Preprocessing maximum distance smallest enclosing circle smallest enclosing ball algorithm complexity preprocessing convex hull convex hull diameter

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A Low-complexity Transceiver Design and Prototype Development for Narrowband IoT 7

A Low-Complexity Transceiver Design and Prototype Developmen...

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7th international conference on Computer and Communication Systems, ICCCS 2022

作者： Zhang, Ruiqi Wu, Peiran Wen, Wenkun Xia, Minghua Sun Yat-sen University School of Electronics and Information Technology Guangzhou510006 China Guangzhou Techphant Co. Ltd. Guangzhou510310 China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

In this paper, a low-complexity transceiver is designed for narrowband Internet-of-things (IoT). Its prototype is developed based on GNU Radio, an open-source software-defined radio development toolkit. To deal with potentially high carrier-frequency offsets and low received signal-to-noise ratio widely occurring in IoT, we adopt the chirp signals as the preamble and the modulation scheme of direct sequence spread spectrum-continuous phase frequency shift keying (DSSS-CPFSK) for the payload. Given this transmitter, the receiver is carefully designed, especially including the frame synchronization and payload demodulation. Afterward, the prototype of this transceiver is implemented in GNU Radio. Finally, simulation results in Matlab and field test ones based on GNU Radio and USRP demonstrate the effectiveness of the proposed design and prototype development. © 2022 IEEE.

关键词： Internet of things

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Benchmarking Classifiers for Loan Default Prediction using Archetypal Analysis 7

Benchmarking Classifiers for Loan Default Prediction using A...

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7th international conference on algorithms, Computing and Systems, ICACS 2023

作者： Antoniadis, Anastasios Georgiou, Konstantinos Charmanas, Konstantinos Mittas, Nikolaos Angelis, Lefteris School of Informatics Aristotle University Greece Department of Chemistry International Hellenic University Greece

ISBN: (纸本)9798400709098

the prediction of loan default is a critical process for the successful development of financial institutions. To effectively manage credit risk, numerous machine learning models have been employed to distinguish creditworthy from high-risk applicants. However, determining an optimal model remains a challenge. To address this, in the current study, we explore an alternative approach for model benchmarking. the main concept involves the usage of a pipeline that constructs different classifiers for loan prediction and compares their performance across several evaluation metrics. To achieve this goal, we deploy an approach based on a multivariate statistical method, known as Archetypal Analysis (AA). the proposed methodology is applied to four datasets with diverse structural characteristics. the findings demonstrate that advanced classifiers like Random Forests (RF) and Artificial Neural Networks (ANN), with oversampling, simple parameter tuning, and feature selection consistently outperform traditional classifiers across most evaluation criteria. In conclusion, the results showcase the ability of AA to intuitively identify the best and worst models for each unique scenario. © 2023 Copyright held by the owner/author(s).

关键词： Forecasting

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Predicting Natural Frequencies of a Cantilever Using Machine Learning 7

Predicting Natural Frequencies of a Cantilever Using Machine...

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7th international conference on Material Strength and Applied Mechanics, MSAM 2024

作者： Horváth, Krisztián Zelei, Ambrus Department of Whole Vehicle Engineering Audi Hungaria Faculty of Automotive Engineering University of Gyor Gyor Hungary

ISBN: (纸本)9781643685472

In the context of structural analysis and design, natural frequencies play a vital role, and their prediction is essential in machine and vehicle design processes. the simulations related to the modal parameters are computationally intensive for systems with large complexity. this paper demonstrates on an illustrative academic example that natural frequencies can be successfully predicted using ML models. this paper aims to develop a model based on machine learning (ML) to predict a simple cantilever's natural frequencies based on the physical parameters of the beam. the independent variables X are the geometric parameters including width, length, and thickness, while the dependent variable Y is the natural frequency. the study is framed using a systematic methodology that covers the stages of data collection, ML model selection, model training and validation. the validation process proves the effectiveness of ML as a computationally cheap replacement for traditional methods of prediction. the current research contributes to the investigation of the usage of commercially available ML tools in structural engineering. We report that the ODYSSEE A-Eye software is capable of natural frequency prediction with a varying geometry structure with less than 4% error for an 80-member training set of cantilever beam with various dimensions. Further developments will include considerations of noise, vibration, and harshness (NVH) to enhance system performance and improve user comfort. © the Author(s), 2024.

关键词： Cantilever beams

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2022 7th international conference on Image, Vision and Computing, ICIVC 2022

2022 7th International Conference on Image, Vision and Compu...

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7th international conference on Image, Vision and Computing, ICIVC 2022

ISBN: (纸本)9781665467346

the proceedings contain 153 papers. the topics discussed include: robust facial expression recognition based on dual branch multi-feature learning;review of human violence recognition algorithms;interlaced perception for person re-identification based on Swin transformer;skeleton-based dumbbell fitness action recognition using two-stream LSTM network;human action recognition based on three-stream network with frame sequence features;combining attention mechanism and dual-stream 3d convolutional neural network for micro-expression recognition;a robust approach for smile recognition via deep convolutional neural networks;a named entity recognition method based on deep learning for Chinese legal documents;modality-independent regression and training for improving multispectral pedestrian detection;textile defect detection algorithm based on unsupervised learning;an optimization scheme of object detection model based on CNN feature visualization method;and a crosswalk stripe detection model based on gradient similarity tags.

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