检索结果-内蒙古大学图书馆

An evolutionary features-based neural grey system model and its application

APPLIED MATHEMATICAL MODELLING 2025年 145卷

作者： Ma, Xin Hao, Yiwu Li, Wanpeng Southwest Univ Sci & Technol Sch Math & Phys Mianyang Peoples R China Univ Aberdeen Dept Comp Sci Aberdeen Scotland

Effectively addressing nonlinear small-sample data has been a critical focus in time-series research. Due to their "black-box" nature and strong reliance on data scale, traditional machine learning models often struggle with such datasets, prompting many studies to adopt neural grey models. However, existing neural grey models frequently suffer from overfitting and limited predictive accuracy. To address these issues, this study integrates the random vector functional link network into grey models for the first time and proposes five evolutionary feature-based training algorithms for the hybrid framework. Through evaluations on five real-world cases using four accuracy metrics, the proposed model which is based on moth-flame optimization algorithm demonstrates superior performance, achieving mean absolute percentage error improvements ranging from 6.5181% to 96.7559% compared to 21 grey models and 15 machine learning models. Additionally, the study reveals that increasing neuron counts and iteration steps enhances model complexity and training time, underscoring the importance of optimizing these parameters for improved performance. This research bridges the gap in random vector functional link network applications for small-sample data and partially alleviates the limitations of neural grey models in terms of overfitting and predictive accuracy.

关键词： Grey system model Random vector functional link networks Evolutionary algorithm Least squares method grid search algorithm

来源：评论

学校读者我要写书评

暂无评论

Increasing the efficiency of selected grid search procedures through the introduction of a best step mechanism

引用

JOURNAL OF HEURISTICS 1999年第2期5卷 199-214页

作者： Falkowski, J Nicholls, MG Swinburne Univ Technol Sch Business Hawthorn Vic 3122 Australia Swinburne Univ Technol Grad Sch Management Hawthorn Vic 3122 Australia

In this paper, several new developments are suggested in order to increase the efficiency of grid search procedures used within vertex enumeration solution algorithms based on both the classical cobweb technique (a two constraint approach) and a single constraint approach. The gains in efficiency (and robustness) are demonstrated by incorporating the developments into a grid search procedure (which is a part of a heuristic solution algorithm used to obtain solutions to a non-linear bi-level multi-period model of an aluminium smelter) and applying it to a test suite of problems. The classical cobweb technique is shown to have some serious problems when used in this application but with step size improvements suggested in the paper, is shown to be very competitive. The developments are also incorporated into a single constraint based approach which does not suffer from the cobweb specific difficulties. The improvements considered include the use of a step mechanism initially with a step size calculated a priori and then finally with a tailored (best) one. The latter development when applied to the cobweb approach, requires the approximation of the two constraints (and hence the intersection of their graphs) using second degree polynomials.

关键词： heuristics grid search algorithm vertex enumeration cobweb search

来源：评论

学校读者我要写书评

暂无评论

grid search as applied to the determination of Mark-Houwink parameters

引用

JOURNAL OF APPLIED POLYMER SCIENCE 2000年第4期76卷 481-487页

作者： Chen, DY Liu, XH Zhou, YP Yang, XJ Lu, LD Wang, X Nanjing Univ Sci & Technol Mat Chem Lab Nanjing 210094 Peoples R China Maanshan Iron & Steel Co Ltd Coking & Chem Co Maanshan 243021 Peoples R China

This article demonstrates the applicability of the algorithm of grid search to the determination of Mark-Houwink (MH) parameters. In the existing methods, the determination of MH parameters involves the use of linear or nonlinear regression. In the cases of using the algorithm of grid search to solve the linear regression problem for the determination of MH parameters, the values of the MH parameters obtained by the grid search method are the same as those obtained by the linear regression method, while in the cases when some nonlinear regression methods have to be used in the existing methods, using the algorithm of grid search can determine the parameters much more easily and accurately than using any nonlinear regression methods. In addition, the grid search method is very easy to understand and execute, and the accuracy of the results can be exhibited by the value of the least-square function. (C) 2000 John Wiley & Sons, Inc.

关键词： grid search algorithm global optimization Mark-Houwink parameters molecular weight

来源：评论

学校读者我要写书评

暂无评论

Gas Pipeline Flow Prediction Model Based on LSTM with grid search Parameter Optimization

引用

PROCESSES 2023年第1期11卷 63页

作者： Liu, Lu Liang, Jing Ma, Li Zhang, Hailin Li, Zheng Liang, Shan Cent Sichuan Dist PetroChina Southwest Oil & Gas F Suining 629000 Peoples R China Minist Educ Key Lab Dependable Serv Comp Cyber Phys Soc Chongqing 400044 Peoples R China Chongqing Univ Coll Automat Chongqing 400044 Peoples R China

Due to the abundant operation data (e.g., pressure, flow rate, and temperature) for natural gas (NG) gathering pipelines provided by the supervisory control and data acquisition (SCADA) system, the machine-learning-based real-time flow prediction has become a critical solution to enable the identification of the abnormality of pipelines, further to guarantee the safe operation of the pipelines. However, traditional machine-learning-based methods cannot always function well due to the temporal characteristics of the SCADA data often being ignored, resulting from a lack of time memory capability. Therefore, this paper proposes a method to automatically perform the feature mining of flow time series by considering the correlation of flow data at both ends of the pipeline, combined with the long short-term memory (LSTM) network. The current and historical data at both pipeline ends are used as input vectors of the LSTM network to predict the terminal output flow at the next moment. Furthermore, to solve the problem that the parameters of the LSTM model are configured with manual experience, a grid search algorithm (GSA) is introduced to optimize the parameters of the LSTM. Consequently, the effectiveness and superiority of the proposed method are carried out in a real-world NG gathering pipeline.

关键词： natural gas pipeline LSTM grid search algorithm parameter optimization flow prediction

来源：评论

学校读者我要写书评

暂无评论

Simultaneous Analysis of Seismic Velocity and Electrical Conductivity in the Crust and the Uppermost Mantle: A Forward Model and Inversion Test Based on grid search

引用

JOURNAL OF GEOPHYSICAL REsearch-SOLID EARTH 2021年第9期126卷 e2021JB022307-e2021JB022307页

作者： Iwamori, Hikaru Ueki, Kenta Hoshide, Takashi Sakuma, Hiroshi Ichiki, Masahiro Watanabe, Tohru Nakamura, Michihiko Nakamura, Hitomi Nishizawa, Tatsuji Nakao, Atsushi Ogawa, Yasuo Kuwatani, Tatsu Nagata, Kenji Okada, Tomomi Takahashi, Eiichi Univ Tokyo Earthquake Res Inst Tokyo Japan Japan Agcy Marine Earth Sci & Technol JAMSTEC Res Inst Marine Geodynam Yokosuka Kanagawa Japan Akita Univ Dept Earth Resource Sci Akita Japan Natl Inst Mat Sci NIMS Res Ctr Funct Mat Tsukuba Ibaraki Japan Tohoku Univ Res Ctr Predict Earthquakes & Volcan Erupt Sendai Miyagi Japan Univ Toyama Dept Earth Syst Sci Toyama Japan Tohoku Univ Dept Earth Sci Sendai Miyagi Japan Natl Inst Adv Ind Sci & Technol Res Inst Earthquake & Volcano Geol Tsukuba Ibaraki Japan Yamanashi Prefectural Govt Mt Fuji Res Inst Fujiyoshida Yamanashi Japan Tokyo Inst Technol Volcan Fluid Res Ctr Tokyo Japan Natl Inst Mat Sci NIMS Res & Serv Div Mat Data & Integrated Syst Tsukuba Ibaraki Japan Chinese Acad Sci Guangzhou Inst Geochem Guangzhou Peoples R China

This study presents a forward model to quantify the P-wave velocity (V-P), S-wave velocity (V-S), and electrical conductivity (sigma) of the solid-liquid mixtures for a given set of pressure, temperature, lithology, liquid phase (aqueous fluid or melt), liquid fraction, and geometrical parameters in relation to the aspect ratio and connectivity of the liquid phase. This is based on previous experimental and theoretical studies on seismic velocity and electrical conductivity of solid rocks and liquid phases. A total of 78 lithologies, an aqueous fluid with NaCl (similar to 0-10 wt.%), and mafic to felsic melt appropriate for the crust and the uppermost mantle conditions were described in terms of V-P, V-S, and sigma, as per previous experimental measurements and molecular dynamics simulation. This forward model is provided as a Windows executable program, and generates synthetic V-P, V-S, and sigma, referring to the seismic velocities and electrical conductivity observed in the northeast Japan arc. After generation of the synthetic V-P, V-S, and sigma, the original lithology and liquid parameters (phase, fraction, aspect ratio, and connectivity) were searched by implementing the grid search algorithm to map the misfit over the broad parameter space. The mapping shows the presence of a global misfit minimum around the optimized solution and the possibility of resolving the lithology and the liquid phase parameters based on the observed V-P, V-S, and sigma by using the forward model presented in this study.

关键词： forward model seismic velocity electrical conductivity solid-liquid mixture joint inversion grid search algorithm

来源：评论

学校读者我要写书评

暂无评论

Remaining useful life prediction for lithium-ion batteries incorporating spatio-temporal information

引用

JOURNAL OF ENERGY STORAGE 2024年 88卷

作者： Lv, Zihao Song, Yi He, Chunlin Xu, Liming China West Normal Univ Sch Elect Informat Engn Nanchong 637009 Peoples R China Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China China West Normal Univ Artificial Intelligence Res Inst Sch Comp Sci Nanchong 637009 Peoples R China

Accurately predicting the remaining useful life (RUL) of lithium -ion batteries (LIBs) is crucial in the field of industrial intelligence. However, existing generalized models face challenges in battery life prediction due to the presence of prevalent noise and limited degradation data. To address this issue, we proposed a spatiotemporally integrated RUL prediction model, namely, the DAE-MSCNN-LSTM model, which leverages the combination of multiscale convolutional neural network (MSCNN) and long -short-term memory network (LSTM). This approach can be used to effectively extract feature information from limited available data. Moreover, the model incorporates a denoising autoencoder (DAE) to refine the raw data by mitigating noise and handling outliers. Subsequently, the processed data are fed into parallel MSCNN and LSTM networks, allowing us to capture both spatial and temporal information. The fused features from these networks are subsequently input into a multilayer perceptron (MLP) for RUL prediction. Additionally, we introduced a unified learning framework to address data denoising and model prediction simultaneously. Finally, the optimal hyperparameters were determined using the grid search algorithm. Through extensive experiments on the NASA and CALCE datasets, the superiority of our proposed LIB RUL prediction for model is demonstrated.

关键词： Deep learning Lithium-ion battery Remaining useful life prediction grid search algorithm Feature engineering

来源：评论

学校读者我要写书评

暂无评论

Statistic evaluation of failure criteria in wellbore stability with temperature effects

引用

FUEL 2019年 252卷 730-752页

作者： Meng, Meng Chen, Pengju Ren, Rui Univ Tulsa Dept Petr Engn Tulsa OK 74104 USA

Geothermal energy is increasingly recognized as a potential of replenishing fossil fuels and meeting decarbonization obligations. HP/HT drilling is also increasingly recognized as a tool to provide an adequate supply of oil/gas. In these two types of activity, the high temperature is the common challenge for drilling. Under high temperature, rocks usually behave differently compared to the ambient condition. Whether the popular failure criteria can be used to evaluate wellbore stability under geothermal conditions is a question which has not been answered yet. In this paper, the triaxial compression tests under different temperature for six types of rock (Strathbogie granite, Tak granite, Tournemire shale, Slate, Carthage marble, and Crab Orchard sandstone) have been used to evaluate six different failure criteria. Two methods have been implemented to obtain rock cohesion and internal friction angle, which are grid search algorithm and Mohr failure line method. Both methods show that Modified Lade is the failure criterion that provides the best performance in predicting rock failure under geothermal drilling. The grid search algorithm guarantees the best performance of the failure criteria, providing with the best-fit rock parameters. The more practical method of Mohr failure line can still generate engineering reasonable predictions if a safety factor of 1.1 is considered, but only the Modified Lade should be used. The thermal influence on rock parameters is also analyzed and the cohesion is found to be decreased with the improvement of temperature, whereas the internal friction angle does not have a consistent relationship with temperature. Overall, considering the considerable variance of depth (several kilometers) and temperature (several hundred degree Celsius) of geothermal and deep oil/gas resources, the Modified Lade has proven to be the best choice to perform wellbore stability analysis.

关键词： Temperature effect grid search algorithm Failure criterion Triaxial compression strength

来源：评论

学校读者我要写书评

暂无评论

Predictive analysis of sell-and-purchase shipping market: A PIMSE approach

引用

TRANSPORTATION REsearch PART E-LOGISTICS AND TRANSPORTATION REVIEW 2024年 185卷

作者： Mo, Jixian Gao, Ruobin Yuen, Kum Fai Bai, Xiwen Renmin Univ China Sch Agr Econ & Rural Dev Beijing 100872 Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn 50 Nanyang Ave Singapore 639798 Singapore Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China 50 Nanyang Ave N1 01b-37 Singapore 639798 Singapore

Estimating second-hand ship prices in the highly uncertain and cyclical ship trading market is a challenge due to its volatile nature. In this study, we propose a novel and highly interpretable model termed as the parsimonious intelligent model search engine (PIMSE), to investigate the relationship between key supply variables and the prices of second-hand oil tankers. Through empirical evaluation using a time series dataset spanning from 2002 to 2020, encompassing three types of oil tankers (VLCC, Suezmax, and Aframax), we assess the effectiveness and performance of PIMSE. The results demonstrate the superior performance of PIMSE compared to other estimation models in terms of its accuracy and stability. It can effectively address abrupt structural change and capture trend and seasonal variations in the time series data. Moreover, the high interpretability of PIMSE provides valuable insights into the factors that influence second-hand ship prices, empowering stakeholders in the shipping industry to make well-informed investment decisions. By leveraging PIMSE, decision-makers can gain a deeper understanding of market dynamics and navigate the complexities of the ship trading industry. Notably, PIMSE's ability to handle the cyclical nature of the ship trading market and incorporate trend and seasonal variations enhances the robustness and accuracy of second-hand ship price estimation.

关键词： grid search algorithm Second-hand tankers Lead -lag structure Time series forecasting

来源：评论

学校读者我要写书评

暂无评论

Predictability of the Physical Shipping Market by Freight Derivatives

引用

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 2023年第1期70卷 267-279页

作者： Duru, Okan Gulay, Emrah Bekiroglu, Korkut Ocean Dynamex Kanata ON K2K 0K9 Canada Dokuz Eylul Univ Econometr Dept TR-35220 Izmir Turkey SUNY Poly Tech Inst Elect Engn Technol Utica NY 13502 USA

This article investigates the predictability of dry bulk shipments' physical shipping costs while testing the predictive significance of derivative products. Accordingly, a comprehensive grid search procedure is needed to simulate combinations of model structures subject to a cross-validation process. In this regard, the intelligent model search engine (IMSE) is implemented as the search algorithm. The IMSE algorithm is selected due to its broad model space naturally consisting most of the traditional econometric model structures and advanced features, such as sample size optimization (also detects structural breaks), lag structure optimization (also reflects seasonality), among others. In contrast to the previous studies in the shipping market research, IMSE executes a relaxation of statistical significance criteria to target the out of sample predictive accuracy (instead of the goodness of fit). Sparsification is retained by utilizing a dropout procedure in line with the cross-validation process. The empirical results indicate the fact that predictive accuracy can be achieved or improved with a shorter sample period. More than half of the entire dataset has not been utilized in the final selections for most simulations. One-month and two-month maturity derivative contracts are tested for predictive features, while none of them is selected for the sparse model selections.

关键词： Predictive models Forecasting Time series analysis Training Optimization search engines Raw materials Commodity market freight derivatives grid search algorithm lead-lag structure predictive analytics

来源：评论

学校读者我要写书评

暂无评论

A new approach to the determination of Mark-Houwink parameters

引用

EUROPEAN POLYMER JOURNAL 2000年第12期36卷 2639-2644页

作者： Chen, DY Wang, HZ Lu, LD Wang, X Nanjing Univ Sci & Technol Mat Chem Lab Nanjing 210094 Peoples R China

A new approach to determining Mark-Houwink (MH) parameters accurately and conveniently is proposed in this paper. With this method, the MH parameters of a polymer system can be determined by firstly measuring the average retention volumes of several polydisperse samples of the polymer system with a gel permeation chromatography (GPC) and their intrinsic viscosities with a Ubbelohde viscometer, then finding a nonlinear least square function according to the least square principle, and finally deciding the global optimum values of the MH parameters accurately and conveniently by grid search algorithm. With this method, the hard work and possible errors due to fractionation of the polydisperse sample of the polymer can be avoided. In addition, this method has two important advantages over existing analogous methods: one is that, this method uses a GPC chromatogram of a polydisperse sample of the polymer system as a whole instead of dividing it into sections and treating each of the sections as a monodisperse sample, thus, the errors arising from the instrumental spreading effect can be avoided;the other is that, the grid search algorithm is used in this method to find the global optimum values of MH parameters in a short time, thus, the errors and the trouble resulting from the application of a nonlinear regression algorithm can be avoided as well. The polymer systems of polystyrene (PS) in toluene at 25 degreesC and poly(methyl methacrylate) (PMMA) in benzene at 25 degreesC have been selected to demonstrate the applicability of this method. In addition, the computer program can be used to all the cases of determining the MH parameters by this method. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： Mark-Houwink parameters grid search algorithm gel permeation chromatography instrumental spreading effect

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：