检索结果-内蒙古大学图书馆

Real-Time Identification of Indoor Pollutant Source Positions Based on Neural Network Locator of Contaminant Sources and Optimized Sensor Networks

引用

JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION 2010年第9期60卷 1034-1048页

作者： Vukovic, Vladimir Tabares-Velasco, Paulo Cesar Srebric, Jelena Penn State Univ Dept Architectural Engn University Pk PA 16802 USA

A growing interest in security and occupant exposure to contaminants revealed a need for fast and reliable identification of contaminant sources during incidental situations. To determine potential contaminant source positions in outdoor environments, current state-of-the-art modeling methods use computational fluid dynamic simulations on parallel processors. In indoor environments, current tools match accidental contaminant distributions with cases from precomputed databases of possible concentration distributions. These methods require intensive computations in pre- and postprocessing. On the other hand, neural networks emerged as a tool for rapid concentration forecasting of outdoor environmental contaminants such as nitrogen oxides or sulfur dioxide. All of these modeling methods depend on the type of sensors used for real-time measurements of contaminant concentrations. A review of the existing sensor technologies revealed that no perfect sensor exists, but intensity of work in this area provides promising results in the near future. The main goal of the presented research study was to extend neural network modeling from the outdoor to the indoor identification of source positions, making this technology applicable to building indoor environments. The developed neural network Locator of Contaminant Sources was also used to optimize number and allocation of contaminant concentration sensors for real-time prediction of indoor contaminant source positions. Such prediction should take place within seconds after receiving real-time contaminant concentration sensor data. For the purpose of neural network training, a multizone program provided distributions of contaminant concentrations for known source positions throughout a test building. Trained networks had an output indicating contaminant source positions based on measured concentrations in different building zones. A validation case based on a real building layout and experimental data demonstrated the ability o

关键词： Studies Indoor air quality Inverse problems Accuracy Buildings optimization algorithms Sensors

来源：评论

学校读者我要写书评

暂无评论

Optimal design of high voltage composite insulators with grading rings in different configurations

引用

ELECTRIC POWER SYSTEMS RESEARCH 2023年第1期221卷

作者： Hussain, Mohammed Khalil Alshadeedi, Bajel Mohammed Univ Baghdad Dept Energy Engn Baghdad Iraq Univ Baghdad Dept Reconstruct & Projects Baghdad Iraq

Reliability of high voltage composite insulators depends on achieving an optimal electrical and geometrical design that produces the lowest electric field strength. This paper proposes a method to find the optimal geometrical design of composite insulators for different voltage levels. The design variables of the insulators include dimensions and locations of sheds and grading rings, as well as physical properties of the insulators. One composite insulator with single grading ring and two with double grading rings are considered and optimized. Considering the complexity of modifying composite insulator parameters to find the lowest electric field strength, five different optimization algorithms are applied and compared to find the optimal geometric design. The main objective of these optimization algorithms to be minimized is the maximum electric field strength, which is calculated using the finite element method-based COMSOL Multiphysics. The results for three different composite insulators under study show that the particle swarm optimization (PSO) algorithm produces the best results in terms of optimal geometrical design to minimize the electric field strength. In addition, the optimal design can reduce not only the electric field strength in clean, uniform pollution and water droplets environmental conditions but also the creepage distance of composite insulators. These improvements in optimized models are achieved without introducing any additional consideration besides the optimal dimensions.

关键词： Composite insulators Maximum electric field strength Uniform pollution Water droplets Finite element method optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Fast flow field prediction over airfoils using deep learning approach

引用

PHYSICS OF FLUIDS 2019年第5期31卷 057103-057103页

作者： Sekar, Vinothkumar Jiang, Qinghua Shu, Chang Khoo, Boo Cheong Natl Univ Singapore Dept Mech Engn 9 Engn Dr 1 Singapore 117575 Singapore

In this paper, a data driven approach is presented for the prediction of incompressible laminar steady flow field over airfoils based on the combination of deep Convolutional Neural Network (CNN) and deep Multilayer Perceptron (MLP). The flow field over an airfoil depends on the airfoil geometry, Reynolds number, and angle of attack. In conventional approaches, Navier-Stokes (NS) equations are solved on a computational mesh with corresponding boundary conditions to obtain the flow solutions, which is a time consuming task. In the present approach, the flow field over an airfoil is approximated as a function of airfoil geometry, Reynolds number, and angle of attack using deep neural networks without solving the NS equations. The present approach consists of two steps. First, CNN is employed to extract the geometrical parameters from airfoil shapes. Then, the extracted geometrical parameters along with Reynolds number and angle of attack are fed as input to the MLP network to obtain an approximate model to predict the flow field. The required database for the network training is generated using the OpenFOAM solver by solving NS equations. Once the training is done, the flow field around an airfoil can be obtained in seconds. From the prediction results, it is evident that the approach is efficient and accurate. Published under license by AIP Publishing.

关键词： Stochastic processes Artificial intelligence optimization algorithms Fluid mechanics Regression analysis Machine learning Artificial neural networks Navier Stokes equations Aerodynamics

来源：评论

学校读者我要写书评

暂无评论

Weibull-like bivariate probability density function and associated estimation algorithms

引用

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2024年第10期53卷 4921-4935页

作者： Saadaoui, Foued King Abdulaziz Univ Fac Sci Dept Stat Jeddah Saudi Arabia Fac Sci Lab LR18ES15 Algebra Number Theory & Nonlinear Ana Monastir Tunisia Univ Sousse Inst Hautes Etud Commerciales IHEC Sousse Tunisia

We propose to introduce a new class of bivariate probability distributions, which we believe is of great interest to statisticians and data scientists. However different from the conventional Weibull it might be, the density function posited herein allows to generalize its properties in two dimensions (2D). This new function, essentially, has structure characteristics and properties different from those of the various bivariate Weibull-type functions found in the literature. The main features, such as the marginal distributions, moments, characteristic functions of this bivariate density are defined. Two related maximum likelihood estimation algorithms are also explicated, tested, and compared. Numerical simulations show the practicality of these algorithms as well as the interest of the new density in several areas of data analysis and extreme values modeling.

关键词： Applied probability COVID-19 data Extreme values modeling optimization algorithms Weibull family

来源：评论

学校读者我要写书评

暂无评论

Distributed-parameter control of the heat source trajectory in thermal materials processing

引用

JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME 1996年第4期118卷 571-578页

作者： Doumanidis, C Fourligkas, N Department of Mechanical Engineering Tufts University Medford MA

In thermal manufacturing processes performed by a localized, sequentially moving heat source, simultaneous regulation of multiple thermal quality characteristics requires real-time control of the temperature field developed through the distributed heat input on the part surface. Such control of the thermal field to a desired distribution employs infrared sensing and feedback of the surface temperature hill, to modulate the torch power and motion in-process. The torch trajectory is guided in real time by an efficient optimization algorithm based on the concept of moving complexes. This distributed-parameter control strategy is developed using a numerical simulation model of thermal processing, and its performance is evaluated experimentally in heat treatment of thin stainless steel plates. The thermal controller is applied to the new scan welding process, in which it drives the torch in a reciprocating motion along the weld, yielding a uniform and smooth temperature field, and thus a favorable material structure and mechanical properties. Application of such thermal control to various other material processing methods is also investigated.

关键词： Welding Reciprocating motion Manufacturing Mechanical properties Materials processing Heat Heat treating (Metalworking) Trajectories (Physics) Plates (structures) Real-time control optimization algorithms Control equipment Feedback Temperature Computer simulation Stainless steel

来源：评论

学校读者我要写书评

暂无评论

k-Means image segmentation using Mumford-Shah model

引用

JOURNAL OF ELECTRONIC IMAGING 2021年第6期30卷 063029-063029页

作者： Shah, Nilima Patel, Dhanesh Franti, Pasi Maharaja Sayajirao Univ Baroda Dept Appl Math Fac Technol & Engn Vadodara Gujarat India Univ Eastern Finland UEF Sch Comp Joensuu Finland

k-Means (KM) is well known for its ease of implementation as a clustering technique. It has been applied for color quantization in RGB, YUV, hyperspectral image, Lab, and other spaces, but this leads to fragmented segments as the pixels are clustered only in the color space without considering connectivity. The problem has been attacked by adding connectivity constraints, or using joint color and spatial features (r, g, b, x, y), which prevent fragmented and nonconvex segments. However, it does not take into account the complexity of the shape itself. The Mumford-Shah model has been earlier used to overcome this problem but with slow and complex mathematical optimization algorithms. We integrate Mumford-Shah model directly into KM context and construct a fast and simple implementation of the algorithm. The proposed approach uses standard KM algorithm with distance function derived from Mumford-Shah model so that it optimizes both the content and the shape of the segments jointly. We demonstrate by experiments that the proposed algorithm provides better results than comparative methods when compared using various error evaluation criteria. The algorithm is applied on 100 images in the Weizmann dataset and two remote sensing images. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License.

关键词： image segmentation clustering k-means Mumford-Shah segmentation optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

A method to calibrate measurement instruments to optimize the spectrometer optics for experiment E94-107 at JLab

引用

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2019年 944卷 162543-162543页

作者： Urciuoli, Gm Cisbani, E. De Leo, R. Garibaldi, F. Higinbotham, D. W. LeRose, J. J. Markowitz, P. Ist Nazl Fis Nucl Sez Roma I-00185 Rome Italy Ist Nazl Fis Nucl Sez Roma I-00161 Rome Italy Ist Super Sanita I-00161 Rome Italy Ist Nazl Fis Nucl Sez Bari I-70125 Bari Italy Univ Bari I-70125 Bari Italy Thomas Jefferson Natl Accelerator Facil Newport News VA 23606 USA Chesapeake Bay Governors Sch Tappahannock VA 22360 USA Florida Int Univ Miami FL 33199 USA

A method to calibrate measurement instruments through the fulfillment of physical laws is described. This method is particularly well suited to determine and/or improve magnetic spectrometer optics databases as well as to establish the best resolution achievable with them. This method was applied to obtain the best resolution achievable in the excitation and binding energy spectra of several hypernuclei produced in the experiment E94-107 performed at JLab, allowing us to obtain sub-MeV resolutions.

关键词： Magnetic spectrometers Optical databases optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies

引用

OPERATIONS RESEARCH 2010年第5期58卷 1269-1286页

作者： Rauner, Marion S. Gutjahr, Walter J. Heidenberger, Kurt Wagner, Joachim Pasia, Joseph Univ Vienna Sch Business & Econ Dept Innovat & Technol Vienna Austria Univ Vienna Sch Business & Econ Dept Stat & Decis Support Syst Vienna Austria Univ Vienna Sch Business & Econ Dept Accounting Vienna Austria Univ Vienna Sch Business & Econ Dept Prod & Operat Management Vienna Austria

We present a risk-group oriented chronic disease progression model embedded within a metaheuristic-based optimization of the policy variables. Policy-makers are provided with Pareto-optimal screening schedules for risk groups by considering cost and effectiveness outcomes as well as budget constraints. The quality of the screening technology depends on risk group, disease stage, and time. As the metaheuristic solution technique, we use the Pareto ant colony optimization (P-ACO) algorithm for multiobjective combinatorial optimization problems, which is based on the ant colony optimization paradigm. Our approach is illustrated by a numerical example for breast cancer. For a 10-year time horizon, we provide cost-effective screening schedules for selected annual and total budgets. We then discuss policy implications of 16 mammography screening scenarios varying the screening schedule (annual, biennial, triennial, quadrennial) and the rate of women tested (25%, 50%, 75%, 100%). Due to the model's flexible structure, interventions for multiple chronic diseases can be considered simultaneously.

关键词： Studies Chronic illnesses Heuristic Decision analysis Pareto optimum optimization algorithms Breast cancer Mammography

来源：评论

学校读者我要写书评

暂无评论

An advanced method for improving the reliability of power losses probabilistic characteristics calculation to determine the optimal wind power capacity and placement tasks

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年 147卷

作者： Andreev, Mikhail Bay, Yuly Kievets, Anton Rudnik, Vladimir Razzhivin, Igor Natl Res Tomsk Polytech Univ Sch Energy & Power Engn Lenina Ave 30 Tomsk 634050 Russia

Due to the trend of increasing electricity consumption that has observed over the past decades, the sustainable development of electric power systems is a relevant task. Taking into account the desire of the leading countries for energy independence, low-carbon energy based on renewable energy sources is being actively penetrated nowadays. One of the main tasks for the renewable energy sources installation into existing electric power systems with no additional changes in network is to maximize power generation with the lowest power losses and to comply with the grid requirements. Considering the stochastic nature of renewable energy, various optimization algorithms are being developed and used for this task. In this regard, numerical methods of deterministic and probabilistic modeling of power systems with, e.g., wind turbine generators are used to determine the optimal placement and capacity. The main problem is that obtaining a reliable result by actual statistical and heuristic methods, based mostly on a group of Monte Carlo methods, does not have a full solution in the whole range of functional dependence, due to the complexity of modeling the input arguments of rare repeatability. As part of the solution to the optimal power flow problems, namely, not exceeding the specified probability density functions of the state parameters, it can lead to false conclusions. This paper proposes a methodology for calculating the probabilistic characteristics of steady-state parameters, increasing the reliability and speed of their calculation by taking into account the values of rare repeatability. The results of research is the refinement of the power flow values (compared with the Monte Carlo method) using the developed method based on selection of interval boundaries of input and output probabilistic data (SIBD method), and the definition of minimum possible power losses as part of the problem of determining the optimal wind power capacity and placement in power system f

关键词： optimization algorithms Probabilistic characteristics Renewable energy sources Uncertainty modeling Wind speed

来源：评论

学校读者我要写书评

暂无评论

Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques-Status and technological review

引用

ELECTRIC POWER SYSTEMS RESEARCH 2020年 178卷 106031-000页

作者： Saddique, Muhammad Shahzar Bhatti, Abdul Rauf Haroon, Shaikh Saaqib Sattar, Muhammad Kashif Amin, Salman Sajjad, Intisar Ali ul Haq, Syed Sadam Awan, Ahmed Bilal Rasheed, Nadia UET Dept Elect Engn Taxila Pakistan GCUF Dept Elect Engn Faisalabad Pakistan Majmaah Univ Coll Engn Dept Elect Engn Majmaah 11952 Saudi Arabia Islamia Univ Bahawalpur UCE&T Dept Comp Syst Engn Bahawalpur Pakistan

Power system operation with proper planning is an utmost task for enhancing the economy of the country. The Optimal Reactive Power Dispatch (ORPD) plays an important task for secure, reliable and optimal operations of power system. ORPD is a complex, non-linear, non-convex, non-continuous and multi-model problem which involves discrete as well as continuous variables. Thus, its solution comprises of different objective functions like improving voltage profile, reducing power losses, voltage stability enhancement and transmission cost minimization. Due to the non-linear nature of problem, most of the techniques applied to ORPD are meta-heuristic. Despite the numerous articles published on these techniques, none has given sufficient emphasis on the comprehensively summarizing the existing meta-heuristic methods for solution of ORPD problem. This work presents a survey of different meta-heuristic techniques applied for solution of ORPD problems in power transmission system. Moreover, a new meta-heuristic Sine-Cosine algorithm is also proposed to solve the problem. A case study is performed where different meta-heuristic techniques are implemented to solve the same problem. Later, statistical analysis is performed to rank all implemented techniques. It is envisaged that the information gathered in this paper will be a valuable one-stop source of information for researchers working on this topic.

关键词： Electric power system operation Power system planning Optimal reactive power dispatch optimization algorithms Meta-heuristic techniques

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：