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Time-series prediction based on global fuzzy measure in social networks

Li-ming YANG,Wei ZHANG,Yun-fang CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第10期页码 805-816 doi: 10.1631/FITEE.1500025

摘要： Social network analysis (SNA) is among the hottest topics of current research. Most measurements of SNA methods are certainty oriented, while in reality, the uncertainties in relationships are widely spread to be overridden. In this paper, fuzzy concept is introduced to model the uncertainty, and a similarity metric is used to build a fuzzy relation model among individuals in the social network. The traditional social network is transformed into a fuzzy network by replacing the traditional relations with fuzzy relation and calculating the global fuzzy measure such as network density and centralization. Finally, the trend of fuzzy network evolution is analyzed and predicted with a fuzzy Markov chain. Experimental results demonstrate that the fuzzy network has more superiority than the traditional network in describing the network evolution process.

关键词： Time-series network Fuzzy network Fuzzy Markov chain

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Employing electricity-consumption monitoring systems and integrative time-series analysis models: A case

Seiya MAKI, Shuichi ASHINA, Minoru FUJII, Tsuyoshi FUJITA, Norio YABE, Kenji UCHIDA, Gito GINTING, Rizaldi BOER, Remi CHANDRAN

《能源前沿（英文）》 2018年第12卷第3期页码 426-439 doi: 10.1007/s11708-018-0560-4

摘要：

The Paris Agreement calls for maintaining a global temperature less than 2°C above the pre-industrial level and pursuing efforts to limit the temperature increase even further to 1.5°C. To realize this objective and promote a low-carbon society, and because energy production and use is the largest source of global greenhouse-gas (GHG) emissions, it is important to efficiently manage energy demand and supply systems. This, in turn, requires theoretical and practical research and innovation in smart energy monitoring technologies, the identification of appropriate methods for detailed time-series analysis, and the application of these technologies at urban and national scales. Further, because developing countries contribute increasing shares of domestic energy consumption, it is important to consider the application of such innovations in these areas. Motivated by the mandates set out in global agreements on climate change and low-carbon societies, this paper focuses on the development of a smart energy monitoring system (SEMS) and its deployment in households and public and commercial sectors in Bogor, Indonesia. An electricity demand prediction model is developed for each device using the Auto-Regression eXogenous model. The real-time SEMS data and time-series clustering to explore similarities in electricity consumption patterns between monitored units, such as residential, public, and commercial buildings, in Bogor is, then, used. These clusters are evaluated using peak demand and Ramadan term characteristics. The resulting energy-prediction models can be used for low-carbon planning.

关键词： electricity monitoring electricity demand prediction multiple-variable time-series modeling time-series cluster analysis Indonesia

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一种基于多因素分析和多模型集成的海洋溶解氧浓度时间序列预测混合神经网络模型 Article

刘辉, 杨睿, 段铸, 吴海平

《工程（英文）》 2021年第7卷第12期页码 1751-1765 doi: 10.1016/j.eng.2020.10.023

摘要：

溶解氧是水产养殖的重要指标，准确预测溶解氧浓度可有效提高水产品质量。本文提出了一种新的溶解氧混合预测模型，该模型包括多因素分析、自适应分解和优化集成三个阶段。首先，考虑到影响溶解氧浓度的因素复杂繁多，采用灰色关联度法筛选出与溶解氧关系最密切的环境因素，多因素的考虑使得模型融合更加有效。其次，运用经验小波变换方法自适应地将溶解氧、水温、盐度和氧饱和度等序列分解为子序列。然后，利用5个基准模型对经验小波变换分解出的子序列进行预测，这五个子预测模型的集成权重通过粒子群优化和引力搜索算法计算得出。最后，通过加权分配得到溶解氧多因素集成模型。来自太平洋岛屿海洋观测系统希洛WQB04站收集的时间序列数据验证了该模型的性能。实验的评价指标包括Nash-Sutcliffe效率系数、Kling-Gupta效率系数、平均绝对百分比误差、误差标准差和决定系数。实例分析表明：①所提出的模型能够获得优异的溶解氧预测结果；②该模型优于文中其他对比模型；③预测模型可用于分析溶解氧变化趋势，便于管理者能够做出更好的决策。

关键词：溶解氧浓度预测时间序列多步预测多因素分析经验小波变化分解多模型优化集成

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Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaosneural network model

LI Xiaodong, ZENG Guangming, HUANG Guohe, LI Jianbing, JIANG Ru

《环境科学与工程前沿（英文）》 2007年第1卷第3期页码 334-338 doi: 10.1007/s11783-007-0057-6

摘要： By predicting influent quantity, a wastewater treatment plant (WWTP) can be well controlled. The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumption that the series was predictable. Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction. Reasonable forecasting results were achieved using this method.

关键词： nonlinear reconstruction WWTP influent characteristic Reasonable forecasting

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Analyzing construction safety through time series methods

Houchen CAO, Yang Miang GOH

《工程管理前沿（英文）》 2019年第6卷第2期页码 262-274 doi: 10.1007/s42524-019-0015-6

摘要： The construction industry produces a large amount of data on a daily basis. However, existing data sets have not been fully exploited in analyzing the safety factors of construction projects. Thus, this work describes how temporal analysis techniques can be applied to improve the safety management of construction data. Various time series (TS) methods were adopted for identifying the leading indicators or predictors of construction accidents. The data set used herein was obtained from a large construction company that is based in Singapore and contains safety inspection scores, accident cases, and project-related data collected from 2008 to 2015. Five projects with complete and sufficient data for temporal analysis were selected from the data set. The filtered data set contained 23 potential leading indicators (predictors or input variables) of accidents (output or dependent variable). TS analyses were used to identify suitable accident predictors for each of the five projects. Subsequently, the selected input variables were used to develop three different TS models for predicting accident occurrences, and the vector error correction model was found to be the best model. It had the lowest root mean squared error value for three of the five projects analyzed. This study provides insights into how construction companies can utilize TS data analysis to identify projects with high risk of accidents.

关键词： time series temporal construction safety leading indicators accident prevention forecasting

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General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

《机械工程前沿（英文）》 2009年第4卷第1期页码 15-24 doi: 10.1007/s11465-009-0015-z

摘要： The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.

关键词： linear and nonlinear autoregressive model system identification time series analysis

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Decomposition analysis of energy-related carbon dioxide emissions in the iron and steel industry in China

Wenqiang SUN, Jiuju CAI, Hai YU, Lei DAI

《环境科学与工程前沿（英文）》 2012年第6卷第2期页码 265-270 doi: 10.1007/s11783-011-0284-8

摘要： This work aims to identify the main factors influencing the energy-related carbon dioxide (CO ) emissions from the iron and steel industry in China during the period of 1995–2007. The logarithmic mean divisia index (LMDI) technique was applied with period-wise analysis and time-series analysis. Changes in energy-related CO emissions were decomposed into four factors: emission factor effect, energy structure effect, energy consumption effect, and the steel production effect. The results show that steel production is the major factor responsible for the rise in CO emissions during the sampling period; on the other hand the energy consumption is the largest contributor to the decrease in CO emissions. To a lesser extent, the emission factor and energy structure effects have both negative and positive contributions to CO emissions, respectively. Policy implications are provided regarding the reduction of CO emissions from the iron and steel industry in China, such as controlling the overgrowth of steel production, improving energy-saving technologies, and introducing low-carbon energy sources into the iron and steel industry.

关键词： carbon dioxide (CO₂) emissions decomposition analysis logarithmic mean divisia index (LMDI) technique time-series analysis

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Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated

《医学前沿（英文）》 2023年第17卷第1期页码 68-74 doi: 10.1007/s11684-022-0955-9

摘要： Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual’s health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique “continuous glucose monitoring” (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.

关键词： complexity of glucose time series continuous glucose monitoring impaired glucose regulation insulin secretion and sensitivity refined composite multi-scale entropy

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Prediction and cause investigation of ozone based on a double-stage attention mechanism recurrent neural network

《环境科学与工程前沿（英文）》 2023年第17卷第2期 doi: 10.1007/s11783-023-1621-4

摘要：

● Used a double-stage attention mechanism model to predict ozone.

关键词： Ozone prediction Deep learning Time series Attention Volatile organic compounds

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最小二乘支持向量机的扩展及其在时间序列预测中的应用

向小东

《中国工程科学》 2008年第10卷第11期页码 89-92

摘要：

根据时间序列近期数据较远期数据包含有更多未来信息的思想，对最小二乘支持向量机预测方法进行了扩展，得到了更具一般性的最小二乘支持向量机预测模型，给出了扩展后的预测模型具体算法。两个时间序列的预测实例表明，扩展后的预测方法获得了更好的预测效果，提升了最小二乘支持向量机预测方法的价值。

关键词：最小二乘支持向量机扩展时间序列预测

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综合空气污染和非适宜温度相关死亡风险构建空气健康指数 Article

张庆丽, 陈仁杰, 印冠锦, 杜喜浩, 孟夏, 邱杨, 阚海东, 周脉耕

《工程（英文）》 2022年第14卷第7期页码 156-162 doi: 10.1016/j.eng.2021.05.006

摘要：

综合的空气健康指数有助于强调多种大气危险因素的健康风险，有利于向公众传达不良大气环境的总体风险。本文试图通过整合我国大气污染和非适宜温度相关的每日死亡风险，建立一种新的空气健康指数（Air Health Index, AHI）。本研究从时间序列模型中获得了暴露-反应系数，通过将 2013—2015 年我国 272个城市大气污染物与非适宜温度相关的超额死亡风险求和，构建了新的AHI。估计了基于总死亡率构建的AHI（“总AHI”）与全死因死亡率的关系，并进一步比较了“总AHI”与“特异性AHI”（基于疾病别死亡率构建）在预测心肺系统疾病死亡率方面的能力。研究发现，空气污染和非适宜温度与28.23%的每日超额死亡率有关，其中23.47%与非适宜温度有关，其余的与PM_2.5（1.12%）、NO₂（2.29%）和O₃（ 2.29%）有关。新的AHI采用了10分制的评分标准，272座城市的平均AHI为6分。AHI与死亡率关系的暴露-反应曲线呈线性，不存在阈值。“总AHI”每增加一个单位，全死因死亡率增加0.84%，心血管疾病、冠心病、中风、呼吸系统疾病和慢性阻塞性肺疾病的死亡率分别增加1.01%、0.98%、1.02%、1.66%和1.71%。使用“总AHI”估计疾病别死亡率风险与使用“特异性AHI”预测的疾病别死亡率风险相似。综上所述，本研究提出的“总AHI”可能是一种有前途的风险交流工具，有利于向公众传达与大气环境有关的健康风险。

关键词：大气污染温度空气健康指数死亡时间序列风险交流

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大型重载支承轴的疲劳裂纹时间序列诊断分析

李学军,宾光富,王裕清

《中国工程科学》 2006年第8卷第4期页码 50-53

摘要：

大型重载支承轴隐蔽部位由于发生不可观测的突发性疲劳断裂，严重影响正常生产，给企业带来重大经济损失；分析这类支承轴的结构特点与振动信号特征之间的关系，运用时序分析方法对振动信号进行建模，并采用残差 $σ_{a}^{2}$ 和归一化残差平方和NRSS作为识别疲劳裂纹状态的特征指标，有效诊断出了支承轴的疲劳裂纹程度。实验结果表明，采用 $σ_{a}^{2}$ 和NRSS作为特征指标的时序分析方法对大型重载支承轴隐蔽部位的疲劳裂纹状态进行诊断，比常规的时频幅值特征分析法更为敏感有效、简便易行，且具备很强的实用性。

关键词：大型重载支承轴隐蔽部位疲劳裂纹时间序列

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Negative weights in network time model

Zoltán A. VATTAI, Levente MÁLYUSZ

《工程管理前沿（英文）》 2022年第9卷第2期页码 268-280 doi: 10.1007/s42524-020-0109-1

摘要： Time does not go backward. A negative duration, such as “time period” at first sight is difficult to interpret. Previous network techniques (CPM/PERT/PDM) did not support negative parameters and/or loops (potentially necessitating recursive calculations) in the model because of the limited computing and data storage capabilities of early computers. Monsieur Roy and John Fondahl implicitly introduced negative weights into network techniques to represent activities with fixed or estimated durations (MPM/PDM). Subsequently, the introduction of negative lead and/or lag times by software developers (IBM) apparently overcome the limitation of not allowing negative time parameters in time model. Referring to general digraph (Event on Node) representation where activities are represented by pairs of nodes and pairwise relative time restrictions are represented by weighted arrows, we can release most restraints in constructing the graph structure (incorporating the dynamic model of the inner logic of time plan), and a surprisingly flexible and handy network model can be developed that provides all the advantages of the abovementioned techniques. This paper aims to review the theoretical possibilities and technical interpretations (and use) of negative weights in network time models and discuss approximately 20 types of time-based restrictions among the activities of construction projects. We focus on pure relative time models, without considering other restrictions (such as calendar data, time-cost trade-off, resource allocation or other constraints).

关键词： graph technique network technique construction management scheduling

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Understanding network travel time reliability with on-demand ride service data

Xiqun (Michael) CHEN, Xiaowei CHEN, Hongyu ZHENG, Chuqiao CHEN

《工程管理前沿（英文）》 2017年第4卷第4期页码 388-398 doi: 10.15302/J-FEM-2017046

摘要： Travel time reliability is of increasing importance for travelers, shippers, and transportation managers because traffic congestion has become worse in major urban areas in recent years. To better evaluate the urban network-wide travel time reliability, five indices based on the emerging on-demand ride service data are proposed: network free flow time rate (NFFTR), network travel time rate (NTTR), network planning time rate (NPTR), network buffer time rate (NBTR), and network buffer time rate index (NBTRI). These indices take into account the probability distribution of the travel time rate (i.e., travel time spent for the unit distance, in min/km) of each origin-destination (OD) pair in the road network. We use real-world data extracted from DiDi-Chuxing, which is the largest on-demand ride service platform in China. For demonstrative purposes, the network-wide travel time reliability of Beijing is analyzed in detail from two dimensions of time and space. The results show that the road network is more unreliable in AM/PM peaks than other time periods, and the most reliable time period is the early morning. Additionally, we can find that the central region is more unreliable than other regions of the city based on the spatial analysis results. The proposed network travel time reliability indices provide insights for the comprehensive evaluation of the road network traffic dynamics and day-to-day travel time variations.

关键词： network travel time reliability on-demand ride services travel time rate OD

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Virtual network embedding based on real-time topological attributes

Jian DING,Tao HUANG,Jiang LIU,Yun-jie LIU

《信息与电子工程前沿（英文）》 2015年第16卷第2期页码 109-118 doi: 10.1631/FITEE.1400147

摘要： As a great challenge of network virtualization, virtual network embedding/mapping is increasingly important. It aims to successfully and efficiently assign the nodes and links of a virtual network (VN) onto a shared substrate network. The problem has been proved to be NP-hard and some heuristic algorithms have been proposed. However, most of the algorithms use only the local information of a node, such as CPU capacity and bandwidth, to determine how to map a VN, without considering the topological attributes which may pose significant impact on the performance of the embedding. In this paper, a new embedding algorithm is proposed based on real-time topological attributes. The concept of betweenness centrality in graph theory is borrowed to sort the nodes of VNs, and the nodes of the substrate network are sorted according to the correlation properties between the former selected and unselected nodes. In this way, node mapping and link mapping can be well coupled. A simulator is built to evaluate the performance of the proposed virtual network embedding (VNE) algorithm. The results show that the new algorithm significantly increases the revenue/cost (R/C) ratio and acceptance ratio as well as reduces the runtime.

关键词： Virtual network embedding (VNE) Real-time topological attributes Betweenness centrality Correlation properties Network virtualization