检索结果-内蒙古大学图书馆

Particle Swarm optimization-Based Multi-Objective Planning Model for Marketing Strategy Decision

JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2024年第16期33卷

作者： Li, Bohan Guo, Qi Univ Illinois Dept Biostat Chicago IL 60607 USA Univ Illinois Dept Business Adm Champaign IL 61820 USA

Intelligent algorithms have shown promise in supporting marketing strategy decisions through data mining. However, existing methods have primarily relied on expertise, lacking autonomous decision-making abilities. Consequently, a marketing strategy decision model based on particle swarm optimization and multi-objective programming is proposed. This study first explores the potential for integrating particle optimization and multi-objective programming models partially, and then assesses the overall effectiveness of each marketing strategy by defining a fitness function. Subsequently, the particle swarm optimization algorithm is employed to search for and optimize decision variables to identify the optimal combination of marketing strategies. Finally, several simulation experiments are conducted using external real data. The research findings indicate that the algorithm's error rate in this study was initially 0.23. However, after 500 training sessions, it decreased to 0.08 and maintained a relatively low level. The proportion of marketing strategy revenue increased by 15.2 percentage points between 0 and 100 training sessions, then remained relatively stable at over 30%. Its revenue proportion continued to rise during the training process, significantly surpassing that of other algorithms.

关键词： Particle swarm optimization multi-objective programming decision-making algorithm optimization

来源：评论

学校读者我要写书评

暂无评论

Optimizing Temporal Data Forecasting for Stiffness-Modulated MEMS Reservoir Computing

引用

IEEE SENSORS JOURNAL 2024年第22期24卷 38092-38101页

作者： Guo, Xiaowei Yang, Wuhao Bai, Yunlong Xiong, Xingyin Wang, Zheng Zou, Xudong Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Transducer Technol Beijing 100045 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China

This study details an advanced method of algorithm optimization, specifically developed for a novel reservoir computing (RC) architecture to forecast temporal information. Our physical RC is implemented using micro-electro-mechanical systems (MEMSs), ingeniously employing stiffness modulation, wherein the input is manifested as stiffness disturbances within a nonlinear resonator. We have eliminated the discretization of data that was typically required in conventional delay-based RC before it is injected into the reservoir. This allows our sensor to process natural signals directly, significantly reducing system complexity and power consumption. Theoretically, this idea is capable of integrating sensing and computing in a single device. Due to simplifications made at the hardware level, its capacity to handle forecasting tasks was initially compromised. To address this, we have applied software-level optimizations, coupled with nonlinearity tuning, to restore its capability for complex forecasting. We rigorously tested the method using data from three different chaotic systems, as well as with real sensor data for dynamic temperature compensation, all of which yielded impressive results. The proposed architecture demonstrates the concept of an intelligent sensor that can handle a variety of tasks and scenes.

关键词： algorithm optimization intelligent sensor nonlinear resonator reservoir computing (RC) algorithm optimization intelligent sensor nonlinear resonator reservoir computing (RC)

来源：评论

学校读者我要写书评

暂无评论

Combinatorial algorithm for Optimizing Wood Waste in Framing Designs

引用

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT-ASCE 2011年第3期137卷 188-197页

作者： Manrique, Juan D. Al-Hussein, Mohamed Bouferguene, Ahmed Safouhi, Hassan Nasseri, Reza Univ Alberta Dept Civil & Environm Engn Hole Sch Construct Markin CNRL Nat Resources Engn Facil 1 080 Edmonton AB T6G 2W2 Canada Univ Alberta Dept Math Edmonton AB T6G 2M7 Canada Landmark Grp Builders Edmonton AB T6E 5J4 Canada 3 011 Markin CNRL Nat Resources Engn Facil Dept Civil & Environm Engn Hole Sch Construct Edmonton AB T6G 2W2 Canada

As a result of elevated labor costs, a shortage of trades personnel, and a lack of efficient construction methods, many construction companies in western Canada waste primary materials. In general, these firms suffer from a lack of effective construction guidelines and process standardizations. This paper focuses on the use of a mathematical algorithm, referred to here in this paper as CUTEX, which maximizes the use of wood materials for platform-framing residential construction. In particular, CUTEX is designed to reduce waste by generating a cutting list for wood studs and sheathing (oriented strand boards-OSB). A combinatorial analysis algorithm has been developed and applied to determine the best cutting procedure for wood stick frame houses. Restrictions, such as nominal lumber dimensions and sizes encountered in the North American market, were taken into account. A two-dimensional optimization for sheathing layout has also been developed to minimize the disposal of OSB boards, making the construction process leaner and more economical. A direct and positive impact on the environment and a reduction in construction costs are expected as a result of reducing the amount of primary materials utilized. DOI: 10.1061/(ASCE)CO.1943-7862.0000117. (c) 2011 American Society of Civil Engineers.

关键词： algorithm optimization Automation Computer-aided drafting (CAD) Computer models Construction materials Cutoffs Frame design

来源：评论

学校读者我要写书评

暂无评论

MTSDet: multi-scale traffic sign detection with attention and path aggregation

引用

APPLIED INTELLIGENCE 2023年第1期53卷 238-250页

作者： Wei, Hongyang Zhang, Qianqian Qian, Yurong Xu, Zheng Han, Jingjing Xinjiang Univ Software Coll Urumqi 830000 Peoples R China Key Lab Signal Detect & Proc Xinjiang Uygur Auton Urumqi 830000 Peoples R China Xinjiang Univ Key Lab Software Engn Urumqi 830000 Peoples R China

To solve the problem that existing traffic signs are not easily detected leading to low detection performance due to their small sizes and external factors such as weather conditions, this paper proposes a traffic sign detection method, MTSDet (Multi-scale Traffic Sign Detection with attention and path aggregation), which focuses on the multi-scale detection problem and effectively improves the detection performance. First, the method efficiently extracts semantic features by introducing the Attention Mechanism Network(AMNet), and then feeds the multi-scale semantic features into Path Aggregation Feature Pyramid Network(PAFPN) for multi-scale feature fusion to obtain multi-scale advanced semantic features. Finally, the multi-scale advanced semantic feature map is deformable interest pooled to effectively enhance the multi-scale object detection modeling capability. In this paper, the above method is validated by two classical datasets, German traffic sign detection dataset and Chinese traffic sign detection dataset, which achieve 92.9% and 94.3% mAP, respectively, and have obvious detection accuracy improvement when compared with other classical advanced algorithms, effectively proving the superiority and generalization of the algorithm in this paper. Code is available at haps://***/why529913/MTSDet

关键词： Computer vision Traffic sign detection Feature extraction and fusion algorithm optimization Convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

A New Precipitation Prediction Method Based on CEEMDAN-IWOA-BP Coupling

引用

WATER RESOURCES MANAGEMENT 2022年第12期36卷 4785-4797页

作者： Liu, Fuping Liu, Ying Yang, Chen Lai, Ruixun North China Univ Water Resources & Elect Power Sch Water Conservancy Zhengzhou 450046 Peoples R China Yellow River Inst Hydraul Res Zhengzhou 450003 Peoples R China

Precipitation is the most basic part of the water cycle process. Aiming at the problem of low prediction accuracy caused by the nonlinear and unstable characteristics of the precipitation series, a new precipitation prediction method based on the CEEMDAN-IWOA-BP coupling model is proposed. This method first uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the original precipitation sequence, and obtains a series of intrinsic mode function (IMF) and residual terms (Res) as inherent potential influencing factors, innovatively introduce TENT chaotic mapping and roulette algorithm to improve the Whale optimization algorithm (WOA), use IMFs and Res as the input of the Improve Whale optimization algorithm (IWOA) to optimize Back Propagation (BP) neural network prediction model, and finally superimpose the predicted values as ultima *** present method was applied to predict the annual precipitation from 1958 to 2017 in Sichuan Province. Compared with the prediction results of other models, the CEEMDAN-IWOA-BP coupled model has significantly improved prediction accuracy than the single model, and the prediction error index is smaller than the BP neural network optimized by the Genetic algorithm (GA) and Particle Swarm optimization (PSO) algorithms, moreover, the optimization accuracy and solving ability are significantly enhanced compared with the unimproved WOA. It can extract the information of complex precipitation series more effectively, and then provide a new method for nonlinear and unstable precipitation time series prediction.

关键词： Precipitation prediction algorithm optimization Complete ensemble empirical mode decomposition with adaptive noise Improve whale optimization algorithm BP neural network

来源：评论

学校读者我要写书评

暂无评论

FAST IMPLEMENTATIONS OF 3D PET RECONSTRUCTION USING VECTOR AND PARALLEL PROGRAMMING TECHNIQUES

引用

IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1993年第4期40卷 1082-1086页

作者： GUERRERO, TM CHERRY, SR DAHLBOM, M RICCI, AR HOFFMAN, EJ UNIV CALIF LOS ANGELES SCH MEDLOS ANGELESCA 90024

Computationally intensive techniques that offer potential clinical use have arisen in nuclear medicine. Examples include iterative reconstruction, 3D PET data acquisition and reconstruction, and 3D image volume manipulation including image registration. One obstacle in achieving clinical acceptance of these techniques is the computational time required. This study focuses on methods to reduce the computation time for 3D PET reconstruction through the use of fast computer hardware, vector and parallel programming techniques, and algorithm optimization. The strengths and weaknesses of i860 microprocessor based workstation accelerator boards are investigated in implementations of 3D PET reconstruction.

关键词： algorithm optimization Three Dimensions Cloning Vectors computational time Parallel programming Nuclear Medicine Fasting program technique

来源：评论

学校读者我要写书评

暂无评论

The nlrx r package: A next-generation framework for reproducible NetLogo model analyses

引用

METHODS IN ECOLOGY AND EVOLUTION 2019年第11期10卷 1854-1863页

作者： Salecker, Jan Sciaini, Marco Meyer, Katrin M. Wiegand, Kerstin Univ Gottingen Dept Ecosyst Modelling Gottingen Germany Univ Goettingen Ctr Biodivers & Sustainable Land Use CBL Gottingen Germany

Agent-based models find wide application in all fields of science where large-scale patterns emerge from properties of individuals. Due to increasing capacities of computing resources it was possible to improve the level of detail and structural realism of next-generation models in recent years. However, this is at the expense of increased model complexity, which requires more efficient tools for model exploration, analysis and documentation that enable reproducibility, repeatability and parallelization. NetLogo is a widely used environment for agent-based model development, but it does not provide sufficient built-in tools for extensive model exploration, such as sensitivity analyses. One tool for controlling NetLogo externally is the r-package RNetLogo. However, this package is not suited for efficient, reproducible research as it has stability and resource allocation issues, is not straightforward to be setup and used on high performance computing clusters and does not provide utilities, such as storing and exchanging metadata, in an easy way. We present the r-package nlrx, which overcomes stability and resource allocation issues by running NetLogo simulations via dynamically created XML experiment files. Class objects make setting up experiments more convenient and helper functions provide many parameter exploration approaches, such as Latin Hypercube designs, Sobol sensitivity analyses or optimization approaches. Output is automatically collected in user-friendly formats and can be post-processed with provided utility functions. nlrx enables reproducibility by storing all relevant information and simulation output of experiments in one r object which can conveniently be archived and shared. We provide a detailed description of the nlrx package functions and the overall workflow. We also present a use case scenario using a NetLogo model, for which we performed a sensitivity analysis and a genetic algorithm optimization. The nlrx package is the first framework fo

关键词： agent-based modelling algorithm optimization individual-based modelling model analysis NetLogo r package reproducible workflow sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Design and implementation of a DSP with multi-level low power strategies for cochlear implants

引用

High Technology Letters 2009年第2期15卷 141-146页

作者：麦宋平 Zhang Chun Chao Jun Wang Zhihua Department of Electronic Engineering Tsinghua University Beijing 100084 P.R. China Institute of Microelectronics Tsinghua University Beijing 100084 P.R. China

This paper presents the design and implementation of a low power digital signal processor （THUCIDSP-1 ） targeting at application for cochlear implants. Multi-level low power strategies including algorithm optimization, operand isolation, clock gating and memory partitioning are adopted in the processor design to reduce the power consumption. Experimental results show that the complexity of the Continuous Interleaved Sampling （CIS） algorithm is reduced by more than 80 % and the power dissipation of the hardware alone is reduced by about 25% with the low power methods. The THUCIDSP-1 prototype, fabricated in 0.18-μm standard CMOS process, consumes only 1.91 mW when executing the CIS algorithm at 3 MHz.

关键词： digital signal processor (DSP) cochlear implant (CI) low power algorithm optimization operand isolation clock gating memory partitioning

来源：评论

学校读者我要写书评

暂无评论

Discrete Method of Images for 3D Radio Propagation Modeling

引用

3D RESEARCH 2016年第3期7卷 1-12页

作者： Novak, Roman Jozef Stefan Inst Dept Commun Syst Ljubljana 1000 Slovenia

Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.

关键词： Method of images 3D radio ray tracing Propagation prediction algorithm optimization

来源：评论

学校读者我要写书评

暂无评论

Application of Improved Genetic K-Means Clustering algorithm in Image Segmentation

Application of Improved Genetic K-Means Clustering Algorithm...

引用

1st International Workshop on Education Technology and Computer Science

作者： Tan, Zhicun Lu, Ruihua Southwest Univ Inst Signal & Informat Proc Chongqing 400715 Peoples R China

ISBN: (纸本)9780769535579

An improved genetic K-means clustering algorithm is proposed and is applied to image segmentation. According to the characteristics of the image, the feature vector of the pixel is properly chosen and the weight factors of the feature vector are adjusted, which enhances the segmentation precision. The selection of conventional genetic algorithm and the modification of mutation operations improve the speed of convergence. Computing time is reduced due to combining the membership matrix with the coding of chromosomes skillfully. The results of the experiments demonstrate that in the image segmentation the proposed algorithm is better than traditional genetic K-means algorithm.

关键词： genetic K-means clustering algorithm image segmentation object function algorithm optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：