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Beyond Pasteur’s Quadrant Model: A New Dynamic Model of Basic Research and its Implementation

Zhang Huiqin, Wang Xin, Wang Xu, Sun Changpu

Strategic Study of CAE 2021, Volume 23, Issue 4,   Pages 145-152 doi: 10.15302/J-SSCAE-2021.04.017

Abstract:

Basic research inspired by national interest is critical for the promotionTherefore, the concept and development law of basic research inspired by national interest should be, applied research, and technology development inspired by national interest.and research integrity, and the decisive role of basic research on the key technologies.Besides, the subjective misguidance of researches inspired by national interest should be avoided.

Keywords： basic research     research inspired by demand     Bush’s linear model of innovation     Pasteur’s quadrant model     dynamic model of basic research     falsifiability    

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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Frontiers in Energy 2014, Volume 8, Issue 2,   Pages 254-260 doi: 10.1007/s11708-014-0302-1

Abstract: The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality

Keywords： quantum-inspired binary firefly algorithm     topological monitor reach area     power quality    

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Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1,   Pages 1-14 doi: 10.1007/s11465-018-0511-0

Abstract: To identify the technologies and methods that can facilitate the development of biologically inspiredcreative designs, this research briefly reviews the existing biological-knowledge-based theories andmethods and examines the application of biological-knowledge-inspired designs in various fields.Afterward, this research thoroughly examines the four dimensions of key technologies that underlie thebiologically inspired design (BID) process.

Keywords： creative design     biologically inspired methods     key technologies    

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3,   Pages 665-681 doi: 10.1007/s11709-021-0713-0

Abstract: The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

Keywords： long contraction scour     prediction     uncertainty     ANFIS model     meta-heuristic algorithm    

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Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 4,   Pages 376-384 doi: 10.1007/s11465-012-0352-1

Abstract: an exhaustive evaluation, we would emphasize more on the new insight by digesting the emerging bio-inspiredAs an alternative, bio-inspired methods or materials may shed light on new innovations.

Keywords： minimally invasive surgery     surgical robotics     haptic feedback     miniaturization     bio-inspiration     bionics    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network     decision tree    

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concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 5,   Pages 435-448 doi: 10.1631/FITEE.1500364

Abstract: To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired

Keywords： Head direction cells (HDCs)     Grid cells (GCs)     Path integration     Bionic navigation    

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Understanding the demand predictability of bike share systems: A station-level analysis

Frontiers of Engineering Management   Pages 551-565 doi: 10.1007/s42524-023-0279-8

Abstract: Predicting demand for bike share systems (BSSs) is critical for both the management of an existing BSSWhile researchers have mainly focused on improving prediction accuracy and analysing demand-influencingUsing Divvy bike-share one-year data from Chicago, USA, we measured demand entropy and quantified thesome stations exhibit high uncertainty (a low entropy of 0.65) and others have almost no check-out demandFindings from this study provide more fundamental understanding of BSS demand prediction, which can help

Keywords： bike share systems     demand prediction     prediction errors     machine learning     entropy    

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Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification

Shuming LIU, Wenjun LIU, Jinduan CHEN, Qi WANG

Frontiers of Environmental Science & Engineering 2012, Volume 6, Issue 2,   Pages 204-212 doi: 10.1007/s11783-011-0364-9

Abstract: A flaw of demand coverage method in solving optimal monitoring stations problem under multiple demandIn the demand coverage method, the demand coverage of each set of monitoring stations is calculated byaccumulating their demand coverage under each demand pattern, and the impact of temporal distributionbetween different time periods or demand patterns is ignored.To overcome this flaw, this paper presents a Demand Coverage Index (DCI) based method.

Keywords： demand coverage     monitoring     optimization     water distribution network     water quality    

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Electricity demand, GDP and employment: evidence from Italy

Cosimo MAGAZZINO

Frontiers in Energy 2014, Volume 8, Issue 1,   Pages 31-40 doi: 10.1007/s11708-014-0296-8

Abstract: This paper applies time series methodologies to examine the causal relationship among electricity demandMoreover, there is a bi-directional Granger causality flow between real per capita GDP and electricity demand; while labor force does not Granger-cause neither real per capita GDP nor electricity demand.This implies that electricity demand and economic growth are jointly determined at the same time for

Keywords： energy policies     electricity demand     GDP     labor force     stationarity     structural breaks     cointegration     causality    

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Scenario analysis of the energy demand and CO

Jihong ZHANG, Jian ZHOU, Guangping HU, Tianhou ZHANG

Frontiers in Energy 2010, Volume 4, Issue 4,   Pages 459-468 doi: 10.1007/s11708-010-0119-5

Abstract: An assessment of the energy demand and the potential for sector-based emission reductions will provideIn this paper, Beijing was selected as a special case for analysis in order to assess the energy demandResults show that in the high motorization-oriented pattern scenario, total energy demand is about 13.94%On the other hand, in the bus and rail transit-oriented scenario, total energy demand is about 11.57%

Keywords： scenario analysis     urban traffic pattern     energy demand     reduction potential    

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Smart residential energy management system for demand response in buildings with energy storage devices

S. L. ARUN, M. P. SELVAN

Frontiers in Energy 2019, Volume 13, Issue 4,   Pages 715-730 doi: 10.1007/s11708-018-0538-2

Abstract: Demand side management (DSM) is one of such smart grid technologies which motivate end users to activelyConsumers are expected to respond (demand response (DR)) in various ways to attain these benefits.discharging) and the amount of power exchange from the battery while considering the variations in consumer demand

Keywords： smart grid     demand side management (DSM)     demand response (DR)     smart building     smart appliances     energy storage    

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Modeling and simulation of industrial water demand of Beijing municipality in China

Shouke WEI, Shafi Noor ISLAM, Alin LEI,

Frontiers of Environmental Science & Engineering 2010, Volume 4, Issue 1,   Pages 91-101 doi: 10.1007/s11783-010-0007-6

Abstract: econometric regression models were established in this study to analyze and predict industrial water demandFour scenarios were designed to simulate and analyze the future uncertainty of industrial water demandThe modeling results for industrial water demand suggested that Beijing industry would face a water deficitbetween 3.06 × 10 min 2008 and 2.77 × 10 m in 2015, though its industrial water demand

Keywords： water scarcity     water demand     water deficit     modeling     industry     scenario     Beijing    

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Applications of thermostatically controlled loads for demand response with the proliferation of variable

Meng SONG, Wei SUN

Frontiers in Energy 2022, Volume 16, Issue 1,   Pages 64-73 doi: 10.1007/s11708-021-0732-5

Abstract: flexibility is desirable with the proliferation of variable renewable resources for balancing supply and demandloads (TCLs) attract tremendous attentions because of their specific thermal inertia capability in demandIn this paper, the bottom-up key technologies of TCLs in DR programs based on the current research have

Keywords： thermostatically controlled load     demand response     renewable energy     power system operation    

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Title Author Date Type Operation

Beyond Pasteur’s Quadrant Model: A New Dynamic Model of Basic Research and its Implementation

Zhang Huiqin, Wang Xin, Wang Xu, Sun Changpu

Journal Article

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

Journal Article

Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

Journal Article

Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Journal Article

Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article

concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

Journal Article

Understanding the demand predictability of bike share systems: A station-level analysis

Journal Article

Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification

Shuming LIU, Wenjun LIU, Jinduan CHEN, Qi WANG

Journal Article

Electricity demand, GDP and employment: evidence from Italy

Cosimo MAGAZZINO

Journal Article

Scenario analysis of the energy demand and CO

Jihong ZHANG, Jian ZHOU, Guangping HU, Tianhou ZHANG

Journal Article

Smart residential energy management system for demand response in buildings with energy storage devices

S. L. ARUN, M. P. SELVAN

Journal Article

Modeling and simulation of industrial water demand of Beijing municipality in China

Shouke WEI, Shafi Noor ISLAM, Alin LEI,

Journal Article

Applications of thermostatically controlled loads for demand response with the proliferation of variable

Meng SONG, Wei SUN

Journal Article