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Robust energy-efficient train speed profile optimization in a scenario-based position–time–speed network

Frontiers of Engineering Management 2021, Volume 8, Issue 4,   Pages 595-614 doi: 10.1007/s42524-021-0173-1

Abstract: Train speed profile optimization is an efficient approach to reducing energy consumption in urban railSpecifically, we first construct a scenario-based position–time–speed (PTS) network by considering resistanceparameters as discrete scenario-based random variables.scenario-based energy consumption is less than the model objective value at network

Keywords： robust train speed profile     percentile reliability model     scenario-based position–time–speed network    

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Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity

Yilei Lu, Yunqing Huang, Siyu Zeng, Can Wang

Frontiers of Environmental Science & Engineering 2020, Volume 14, Issue 2, doi: 10.1007/s11783-019-1200-x

Abstract: Impact of urban development on water system is assessed with carrying capacity. Impacts on both water resource quantity and environmental quality are involved. Multi-objective optimization revealing system trade-off facilitate the regulation. Efficiency, scale and structure of urban development are regulated in two stages. A roadmap approaching more sustainable development is provided for the case city. Environmental impact assessments and subsequent regulation measures of urban development plans are critical to human progress toward sustainability, since these plans set the scale and structure targets of future socioeconomic development. A three-step methodology for assessing and optimizing an urban development plan focusing on its impacts on the water system was developed. The methodology first predicted the pressure on the water system caused by implementation of the plan under distinct scenarios, then compared the pressure with the carrying capacity threshold to verify the system status; finally, a multi-objective optimization method was used to propose regulation solutions. The methodology enabled evaluation of the water system carrying state, taking socioeconomic development uncertainties into account, and multiple sets of improvement measures under different decisionmaker preferences were generated. The methodology was applied in the case of Zhoushan city in South-east China. The assessment results showed that overloading problems occurred in 11 out of the 13 zones in Zhoushan, with the potential pressure varying from 1.1 to 18.3 times the carrying capacity. As a basic regulation measure, an environmental efficiency upgrade could relieve the overloading in 4 zones and reduce 9%‒63% of the pressure. The optimization of industrial development showed that the pressure could be controlled under the carrying capacity threshold if the planned scale was reduced by 24% and the industrial structure was transformed. Various regulation schemes including a more suitable scale and structure with necessary efficiency standards are provided for decisionmakers that can help the case city approach a more sustainable development pattern.

Keywords： Urban development plan     Urban water system     Carrying capacity     Scenario analysis     Multi-objective optimization    

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Managing obsolescence of embedded hardware and software in secure and trusted systems

Zachary A. COLLIER, James H. LAMBERT

Frontiers of Engineering Management 2020, Volume 7, Issue 2,   Pages 172-181 doi: 10.1007/s42524-019-0032-5

Abstract: Obsolescence of integrated systems which contain hardware and software is a problem that affects multiple industries and can occur for many reasons, including technological, economic, organizational, and social factors. It is especially acute in products and systems that have long life cycles, where a high rate of technological innovation of the subcomponents result in a mismatch in life cycles between the components and the systems. While several approaches for obsolescence forecasting exist, they often require data that may not be available. This paper describes an approach using non-probabilistic scenarios coupled with decision analysis to investigate how particular scenarios influence priority setting for products and systems. Scenarios are generated from a list of emergent and future conditions related to obsolescence. The key result is an identification of the most and least disruptive scenarios to the decision maker’s priorities. An example is presented related to the selection of technologies for energy islanding, which demonstrates the methodology using six obsolescence scenarios. The paper should be of broad interest to scholars and practitioners engaged with enterprise risk management and similar challenges of large-scale systems.

Keywords： enterprise risk management     diminishing manufacturing sources and material shortages     scenario-based preferences    

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Real-time tool condition monitoring method based on temperature measurement and artificial neural network

Frontiers of Mechanical Engineering doi: 10.1007/s11465-021-0661-3

Abstract: Here, a real-time tool condition monitoring method integrated in an in situ fiber optic temperatureThe spectrum features are then selected and input into the artificial neural network for classificationFurthermore, an application program with a graphical user interface is constructed to present real-time

Keywords： tool condition monitoring     cutting temperature     neural network     learning rate adaption    

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Virtual network embedding based on real-time topological attributes

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

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 2,   Pages 109-118 doi: 10.1631/FITEE.1400147

Abstract: As a great challenge of network virtualization, virtual network embedding/mapping is increasingly importantIt aims to successfully and efficiently assign the nodes and links of a virtual network (VN) onto a sharedsubstrate network.In this paper, a new embedding algorithm is proposed based on real-time topological attributes.A simulator is built to evaluate the performance of the proposed virtual network embedding (VNE) algorithm

Keywords： Virtual network embedding (VNE)     Real-time topological attributes     Betweenness centrality     Correlationproperties     Network virtualization    

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

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

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 10,   Pages 805-816 doi: 10.1631/FITEE.1500025

Abstract: Social network analysis (SNA) is among the hottest topics of current research.The traditional social network is transformed into a fuzzy network by replacing the traditional relationsFinally, 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 networkin describing the network evolution process.

Keywords： Time-series network     Fuzzy network     Fuzzy Markov chain    

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WEIS wheel speed real-time measuring method for VOSM

Mengyao PAN, Guixiong LIU, Xiaobin HONG, Tusheng LIN,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 3,   Pages 322-327 doi: 10.1007/s11465-010-0022-0

Abstract: Wheel speed is one of the key parameters of vehicle operating attitude.To solve the problems in traditional wheel speed measuring methods, such as low measurement precisionand the lack of real-time monitoring of the vehicle’s operating attitude, a wheel embedded intelligentpacket to implement wavelet de-noising for the non-stationary acceleration signals, and adopting short-time;2.05%, and the speed measuring response time is 0.45 s.

Keywords： wheel embedded     intelligent sensing     wheel speed     monitoring    

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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

Frontiers of Environmental Science & Engineering 2007, Volume 1, Issue 3,   Pages 334-338 doi: 10.1007/s11783-007-0057-6

Abstract: The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumptionBased on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built

Keywords： nonlinear     reconstruction     WWTP influent     characteristic     Reasonable forecasting    

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Air-bearing position optimization based on dynamic characteristics of ultra-precision linear stages

CHEN Xuedong, LI Zhixin

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 4,   Pages 400-407 doi: 10.1007/s11465-008-0060-z

Abstract: characteristics including mode frequency, mode shape, and response amplitude are obviously changed with the positionThe combined optimization method is used to optimize the air-bearings position.The method can be generalized to the connection position of different components in manufacture elementsand to implement the system dynamic characteristics optimization when the connection position can be

Keywords： manufacture     different     interaction     air-bearings     response amplitude    

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Negative weights in network time model

Zoltán A. VATTAI, Levente MÁLYUSZ

Frontiers of Engineering Management 2022, Volume 9, Issue 2,   Pages 268-280 doi: 10.1007/s42524-020-0109-1

Abstract: Time does not go backward.Previous network techniques (CPM/PERT/PDM) did not support negative parameters and/or loops (potentiallyMonsieur Roy and John Fondahl implicitly introduced negative weights into network techniques to representreview the theoretical possibilities and technical interpretations (and use) of negative weights in networktime models and discuss approximately 20 types of time-based restrictions among the activities of construction

Keywords： graph technique     network technique     construction management     scheduling    

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

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 2, doi: 10.1007/s11783-023-1621-4

Abstract:

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

Keywords： Ozone prediction     Deep learning     Time series     Attention     Volatile organic compounds    

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

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

Frontiers of Engineering Management 2017, Volume 4, Issue 4,   Pages 388-398 doi: 10.15302/J-FEM-2017046

Abstract: To better evaluate the urban network-wide travel time reliability, five indices based on the emergingon-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 timeAdditionally, we can find that the central region is more unreliable than other regions of the city basedof the road network traffic dynamics and day-to-day travel time variations.

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

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Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images Research Article

Xiaolong CHEN, Xiaoqian MU, Jian GUAN, Ningbo LIU, Wei ZHOU,cxlcxl1209@163.com,guanjian_68@163.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 630-643 doi: 10.1631/FITEE.2000611

Abstract: As a classic deep learning target detection algorithm, Faster R-CNN (region convolutional neural networkIn this paper, taking PPI images as an example, a method based on the Marine-Faster R-CNN algorithmfalse alarm rate, Faster R-CNN was optimized as the Marine-Faster R-CNN in five respects: new backbone network

Keywords： Marine target detection     Navigation radar     Plane position indicator (PPI) images     Convolutional neuralnetwork (CNN)     Faster R-CNN (region convolutional neural network) method    

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PD pattern recognition based on multi-fractal dimension in GIS

ZHANG Xiaoxing, YAO Yao, TANG Ju, ZHOU Qian, XU Zhongrong

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 3,   Pages 270-275 doi: 10.1007/s11465-008-0042-1

Abstract: This paper designs four types of gas insulated substation (GIS) defect models based on partial dischargeThe GIS gray intensity images are constructed based on the mass specimens gathered by the ultra-highfrequency and high-speed sampling systems.The GIS gray intensity images distillation methods, based on multi-fractal characteristics, is put forwardThe characteristic variables are then classified by the radial basis function (RBF) network.

Keywords： substation     high-speed     discharge centrobaric     network     ultra-high frequency    

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Data-driven approach to solve vertical drain under time-dependent loading

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3,   Pages 696-711 doi: 10.1007/s11709-021-0727-7

Abstract: Currently, the vertical drain consolidation problem is solved by numerous analytical solutions, such as time-dependentThus, in this study, a new hybrid model based on deep neural networks (DNNs), particle swarm optimizationand DNN–GA prediction models with three different radial drainage patterns in the smear zone under time-dependent

Keywords： vertical drain     artificial neural network     time-dependent loading     deep learning network     genetic algorithm    

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Title Author Date Type Operation

Robust energy-efficient train speed profile optimization in a scenario-based position–time–speed network

Journal Article

Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity

Yilei Lu, Yunqing Huang, Siyu Zeng, Can Wang

Journal Article

Managing obsolescence of embedded hardware and software in secure and trusted systems

Zachary A. COLLIER, James H. LAMBERT

Journal Article

Real-time tool condition monitoring method based on temperature measurement and artificial neural network

Journal Article

Virtual network embedding based on real-time topological attributes

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

Journal Article

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

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

Journal Article

WEIS wheel speed real-time measuring method for VOSM

Mengyao PAN, Guixiong LIU, Xiaobin HONG, Tusheng LIN,

Journal Article

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

Journal Article

Air-bearing position optimization based on dynamic characteristics of ultra-precision linear stages

CHEN Xuedong, LI Zhixin

Journal Article

Negative weights in network time model

Zoltán A. VATTAI, Levente MÁLYUSZ

Journal Article

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

Journal Article

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

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

Journal Article

Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images

Xiaolong CHEN, Xiaoqian MU, Jian GUAN, Ningbo LIU, Wei ZHOU,cxlcxl1209@163.com,guanjian_68@163.com

Journal Article

PD pattern recognition based on multi-fractal dimension in GIS

ZHANG Xiaoxing, YAO Yao, TANG Ju, ZHOU Qian, XU Zhongrong

Journal Article

Data-driven approach to solve vertical drain under time-dependent loading

Journal Article