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检索条件"主题词=approximation Algorithms"

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Controlling the Reliability of Measuring Channels in Automated Monitoring Systems

Controlling the Reliability of Measuring Channels in Automat...

引用

International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Andrey N. Krasnov Gennady Yu. Kolovertnov Marina Yu. Prakhova Department of automation telecommunications and metrology Ufa State Petroleum Technological University Ufa Russian Federation

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

The development of automation systems for the production facilities of the oil and gas sector comprises several paths, one of which is the introduction of automated monitoring systems that can perform technical diagnostics of the facility in real-time. In many cases, using these systems can improve the reliability of the facility's operations and, in some cases, it facilitates the transition to low-staffed operations. The efficiency of these systems depends on the reliability of the data transferred over measuring channels. This article presents a reliability-control algorithm based on the direct and reverse facility models. It can identify partial probe failures, i.e. the loss of metrological reliability, based on the invariance tests of some parameters, as well as the changes in the parameters of the facility considered. Model construction uses the statistics obtained in normal, pre-emergency, and emergency operating modes of a fuel pump station. Model verification confirmed its adequacy. Using the algorithms considered as additional measuring channel control tools is recommended for any facility.

关键词： Fault diagnosis Visualization Process control approximation algorithms Reliability engineering Real-time systems Mathematical models

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Extending GPU Ray-Tracing Units for Hierarchical Search Acceleration

Extending GPU Ray-Tracing Units for Hierarchical Search Acce...

引用

IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Aaron Barnes Fangjia Shen Timothy G. Rogers Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9798350350579

ISBN: (纸本)9798350350586

Specialized ray-tracing acceleration units have become a common feature in GPU hardware, enabling real-time ray-tracing of complex scenes for the first time. The ray-tracing unit accelerates the traversal of a hierarchical tree data structure called a bounding volume hierarchy to determine whether rays have intersected triangle primitives. Hierarchical search algorithms are a fundamental software pattern common in many important domains, such as recommendation systems and point cloud registration, but are difficult for GPUs to accelerate because they are characterized by extensive branching and recursion. The ray-tracing unit overcomes these limitations with specialized hardware to traverse hierarchical data structures efficiently, but is mired by a highly specialized graphics API, which is not readily adaptable to general-purpose computation. We present the Hierarchical Search Unit (HSU), a flexible datapath to accelerate a more general class of hierarchical search algorithms, of which ray-tracing is one. We synthesize a baseline ray-intersection datapath and maximize functional unit reuse while extending the ray-tracing unit to support additional computations and a more general set of instructions. We demonstrate that the unit can improve the performance of three hierarchical search data structures in approximate nearest neighbors search algorithms and a B-tree key-value store index. For a minimal extension to the existing unit, our HSU improves the state-of-the-art GPU approximate nearest neighbor implementation by an average of 24.8% using the GPU's general computing interface.

关键词： Tree data structures Software algorithms Graphics processing units Ray tracing approximation algorithms Search problems Hardware Software Standards Recommender systems

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Finite-Length Coding Bounds via Guesswork

Finite-Length Coding Bounds via Guesswork

引用

Annual Allerton Conference on Communication, Control, and Computing

作者： Alexander Mariona Ken R. Duffy Muriel Médard Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA USA Dept. of ECE and Dept. of Mathematics Northeastern University Boston MA USA

ISBN: (数字)9798331541033

ISBN: (纸本)9798331541040

Existing bounds on the maximum channel coding rate achievable at finite block lengths are not always meaningful at moderate lengths and for low-noise channels, even when the channel model is simple. We offer a new framework for deriving achievability and converse bounds, along with a simple and accurate approximation, based on guesswork and the GRAND family of decoding algorithms. This approach is theoretically applicable to any channel model; we use it to produce implicit but computable bounds for the binary symmetric channel and the binary additive white Gaussian noise channel. Our approach for the latter is based on a 1-bit quantization of the soft information and offers quantitative insight into the marginal value of this amount of information compared to hard decision and full soft information decoding. For moderate lengths and low-noise settings, our results for both channel models improve on the state-of-the-art.

关键词： Analytical models Adaptation models Quantization (signal) Accuracy Computational modeling approximation algorithms Decoding Channel models Channel coding

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The Optimization of TSK Regression Model by FCM, Droprule and Lion

The Optimization of TSK Regression Model by FCM, Droprule an...

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International Symposium on Computer Science and Intelligent Controls (ISCSIC)

作者： Yuhong Qin Likui Wang School of Artificial Intelligence Control Engineering Technology Innovation Center of Hebei Province Hebei University of Technology Tianjin China

ISBN: (数字)9798350380286

ISBN: (纸本)9798350380293

TSK (Takagi-Sugeno-Kang) fuzzy system is widely used because of its good approximation performance. In order to effectively optimize the regression problem of TSK fuzzy system, based on the recently proposed MBGD-RDA (mini-batch gradient descent with regularization, DropRule and AdaBound) algorithm, we also propose the FCM-Lion (Fuzzy c means with DropRule and Lion) algorithm. The algorithm uses FCM to cluster the input samples to obtain the required number of rules, thus avoiding the problem of rule explosion caused by the shared rule base. In addition, it combines the latest proposed lion (EvoLved Sign Momentum) optimizer to replace the AdaBound algorithm, becouse Lion uses sign function to ignore the length of the gradient and only retains the direction of the gradient, thus playing a regularization effect in optimization process. And since lion only maintains a momentum information, it consumes less memory, so our paper combines it with DropRule to further accelerate parameter optimization. The algorithm we proposed is compared with other four optimization algorithms to prove its superiority by experimenting on six regression datasets with different sizes and dimensions. The results show that the RMSEtest of FCM-Lion is basically the smallest, and the training time is lower than the other four algorithms, which proves the effectiveness of our proposed algorithm.

关键词： Training Computer science Memory management Clustering algorithms approximation algorithms Explosions Takagi-Sugeno model Optimization Fuzzy systems Intelligent control

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Variable Neighborhood Search for Scheduling of Cold Rolling Annealing Process of Silicon Steel*

Variable Neighborhood Search for Scheduling of Cold Rolling ...

引用

International Conference on Industrial Artificial Intelligence (IAI)

作者： Ying Huang Shixin Liu Informatization Business Department Shanghai Baosight Software Limited Company Shanghai China College of Information Science & Engineering Northeastern University Shenyang China

ISBN: (数字)9798350356618

ISBN: (纸本)9798350356625

Aiming at the production scheduling problem of cold rolling annealing process of silicon steel, a multi-objective optimization model of production scheduling is established, which considered various process constraints such as steel grade switch, width jump, annealing temperature jump, etc. The multi-objective functions are transformed into a single objective function by weighted sum method. Based on the characteristics of the problem, four kinds of neighborhood structures for local search are proposed. And a variable neighborhood search algorithm is proposed to solve the problem. The correctness of the model and the effectiveness of the algorithm are verified by practical production instances. The experimental results show that the approximate Pareto solution set with good distribution can be obtained by using the weighted sum method and solved by the variable neighborhood search algorithm proposed in this paper.

关键词： Annealing Job shop scheduling Optimization models Production approximation algorithms Search problems Linear programming Silicon Steel Optimization

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Multi-Objective Derivative-Free Optimization Based on Hessian-Aware Gaussian Smoothing Method

Multi-Objective Derivative-Free Optimization Based on Hessia...

引用

International Conference on Control and Automation (ICCA)

作者： Ran Chen Yuzhe Li Tianyou Chai State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Most deterministic multi-objective optimization algorithms assume that the analytical objective functions and multi-objective gradients are available. However, there may be no available or explicit mathematical model for many real-world optimization problems. These problems are difficult to handle since the evaluations of gradients are inexact or even infeasible, which are termed derivative-free (or zeroth-order) optimization problems. To tackle the issues, a multi-objective derivative-free optimization based on Hessian-aware Gaussian smoothing method is proposed. We evaluate the multi-objective descent direction and produce new candidates for searching the Pareto front. Furthermore, we analyze the corresponding convergence rate of candidates produced by the Hessian-aware Gaussian smoothing method explicitly. Finally, we compared different multi-objective optimization algorithms and illustrated their performance on numerical benchmarks to show the proposed algorithm's effectiveness.

关键词： Measurement Sufficient conditions Smoothing methods Heuristic algorithms Estimation approximation algorithms Linear programming

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Optimal Scheduling of Multi-Source Multi-Destination Links in Multi-UAV Assisted Ad Hoc Networks

Optimal Scheduling of Multi-Source Multi-Destination Links i...

引用

International Conference on Computer and Communications (ICCC)

作者： Jinwei Wang Renhui Xu Laixian Peng Xingchen Wei Sheng Qi College of Communications Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

Unmanned aerial vehicles (UAVs) acting as relays provide new opportunities for assisted wireless communications. However, in a multi-UAV-assisted multi-source multi-destination communication network, there are many challenges in achieving parallel data transmission of multiple source-destination (S-D) pairs and maximizing the throughput of the entire network. To this end, this paper comprehensively considers the influence of interference and noise between source nodes and between relay UAVs, and proposes a source-to-UAV and UAV-to-destination joint link scheduling optimization problem to maximize the throughput of the entire communication network. To solve the optimization problem, this paper also proposes two optimization matching algorithms namely Global Optimal Precision Matching (GOPM) and Dual-order KM Optimized Matching (DKOM). Simulation results show that the two optimization matching algorithms effectively improve network throughput in scenarios with parallel transmission of multiple S-D pairs. In addition, with the increase of network scale, two algorithms show similar performance.

关键词： Wireless communication Simulation Noise Optimal scheduling Interference Throughput approximation algorithms Data communication Communication networks Relays

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Reliability-Aware Network Slicing based on Multi-Objective Optimization

Reliability-Aware Network Slicing based on Multi-Objective O...

引用

Congress on Evolutionary Computation

作者： Qiqi Xia Jin Wang Chengqiang Huang Xin Yao Research Institute of Trustworthy Autonomous Systems (RITAS) Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Reliability Technology Lab Huawei Technologies Co. Ltd. Shenzhen China Department of Computing and Decision Sciences Lingnan University Hong Kong SAR China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Network slicing is an essential technology in 5G and the forthcoming 6G networks. It aims to embed multiple virtual networks, i.e., network slices, on top of a shared substrate network to meet diverse service requirements. While a considerable body of existing research strives to maximize overall profits by meeting the resource demands of the network slices, optimizing their reliability is frequently overlooked. In this paper, we formalize the network slicing problem as a multi-objective optimization problem that aims to maximize total profits and reliability of network slices. To tackle this problem, we propose a new multi-objective optimization approach that improves over the state-of-the-art algorithm, which can achieve good approximate Pareto front results balancing total profits and reliability of network slices. The performance of our proposed method is evaluated on both artificial and real-world network topologies. Experimental results demonstrate the superior performance of our proposed method compared to the baseline algorithm, outperforming the latter in 92% of instances in terms of the Hypervolume (HV) metric.

关键词： Measurement 6G mobile communication Costs Network topology Network slicing Evolutionary computation approximation algorithms

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Beamforming Design of ISAC System for Enhancing Sensing Distance

Beamforming Design of ISAC System for Enhancing Sensing Dist...

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Future Communications and Networks (FCN), International Conference on

作者： Yuan Liu Ruihong Jiang Yongdong Zhu Bin Yang Shuyuan Zhao Research Center for Space Computing System Zhejiang Laboratory Hangzhou China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798331512880

ISBN: (纸本)9798331512897

In this paper, a dual-functionality base station (BS) integrated sensing and communication (ISAC) is exploited to sense one intended target and communicate with multiple users simultaneously. Meanwhile, rate splitting multiple access (RSMA) technology is used to improve communication quality. We formalize a problem aimed at maximizing sensing distance by optimizing the beamforming design of the BS and the allocation of common rate portions, where the signal to interference plus noise ratio (SINR) gain constraint of sensing echo signal and the individual communication rate requirements of each user are satisfied. Due to the non-convexity of the formulated problem, a successive convex approximation (SCA)-based algorithm is proposed to tackle it. Simulation results manifest that as the transmit power increases, the achievable sensing distance increases, and as the SINR threshold of the sensing echo signal increases, the achievable sensing distance decrease. Furthermore, it indicates that the RSMA-based protocol offers superior sensing distance gain compared to the SDMA-based protocol. This performance advantage becomes more pronounced when the communication rate threshold is high, resulting in a relatively large performance gap between the two protocols.

关键词： Base stations Protocols Array signal processing Simulation Interference Integrated sensing and communication approximation algorithms Resource management Iterative methods Signal to noise ratio

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Traffic Simulations: Multi-City Calibration of Metropolitan Highway Networks

Traffic Simulations: Multi-City Calibration of Metropolitan ...

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International Conference on Intelligent Transportation

作者： Chao Zhang Yechen Li Neha Arora Damien Pierce Carolina Osorio Google Research Mountain View CA USA HEC Montreal Mountain View QC Canada

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

This paper proposes an approach to perform travel demand calibration for high-resolution stochastic traffic simulators. It employs abundant travel times at the path-level, departing from the standard practice of resorting to scarce segment-level sensor counts. The proposed approach is shown to tackle high-dimensional instances in a sample-efficient way. For the first time, case studies on 6 metropolitan highway networks are carried out, considering a total of 54 calibration scenarios. This is the first work to show the ability of a calibration algorithm to systematically scale across networks. Compared to the state-of-the-art simultaneous perturbation stochastic approximation (SPSA) algorithm, the proposed approach enhances fit to field data by an average 43.5% with a maximum improvement of 80.0%, and does so within fewer simulation calls.

关键词： Road transportation Perturbation methods Urban areas Traffic control Benchmark testing approximation algorithms Robustness Calibration Standards Intelligent transportation systems

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