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Knowledge growth in university-industry innovation networks - Results from a simulation study

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 2020年 151卷 119746-119746页

作者： Mao, Chongfeng Yu, Xianyun Zhou, Qing Harms, Rainer Fang, Gang Hangzhou Dianzi Univ Coll Econ Hangzhou 310018 Peoples R China Hangzhou Dianzi Univ Sch Management Hangzhou 310018 Peoples R China Univ Twente BMS NIKOS NL-7500 AE Enschede Netherlands Natl Res Univ Higher Sch Econ Moscow 123592 Russia

University-industry innovation networks (UIINs) are important agents of innovation, as they bring together the unique profiles of higher education and industry partners. Knowledge growth in these networks does not happen automatically. We analyze the impact of network density and heterogeneity on knowledge growth in UTINs. Knowledge grows through knowledge transfer, spillover, and knowledge innovation. Knowledge growth is a function of each agent's initial knowledge level, network density, and agent heterogeneity. To analyze these correlates of knowledge growth, we use a knowledge growth model based on multiple agents and simulate knowledge growth in a UIIN. Our results show that network density positively influences knowledge growth. Initially, this positive impact increases and then disappears with a further increase in network density. We also find that heterogeneity moderates the relationship between density and knowledge growth. Through the positive moderating effect of its impact on knowledge innovation, it promotes new knowledge generation in the entire innovation network, thus providing a basis for subsequent knowledge transfer. Our study supports and enriches the contingency view of knowledge growth in innovation networks.

关键词： Network density Network heterogeneity Knowledge growth Knowledge transfer Knowledge innovation agent-based modeling and simulation

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Optimal Allocation Planning for Public EV Charging Station Considering AC and DC Integrated Chargers

Optimal Allocation Planning for Public EV Charging Station C...

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Applied Energy Symposium and Summit - Renewable Energy Integration with Mini/Microgrid (REM)

作者： Liu, Xiyuan Bie, Zhaohong Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Smart Grid Key Lab Shaanxi Prov Xian 710049 Shaanxi Peoples R China

The adoption of AC and DC integrated charger(ADC) is considered as a mean to increase the comprehensive utilization rate and reduce the total cost of charging stations. In this paper a simulation-based optimization framework is proposed to solve the allocation problem for public charging stations equipped with multi-type of facilities, including AC slow chargers(ACCs), DC rapid chargers(DCCs) and ADCs. First of all, the characteristics of AC and DC charging demand are predicted, considering private EVs(PEVs) and electric taxis(TEVs). Then a stochastic queuing and service simulation model of multi-type chargers is developed based on agent-based modeling and simulation(ABMS) method, in order to model the complicated interactions among different types of EVs and chargers in detail. On the basis of the simulation model, an allocation optimization model is formulated to minimize the comprehensive annual cost, including charger investment cost, land purchase cost, grid reinforcement cost and queuing time cost. The simulation-based allocation optimization model is solved by embedded the simulation model as a black box into the meta-heuristics solver engine OptQuest. The proposed optimization framework is implemented in different allocation planning scenarios under different situations. The effects of ADC adoption in public charging stations are discussed by comparing the optimal plans with and without ADCs. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： Electric Vehicle Charging facility allocation planning AC and DC Integrated Charger agent-based modeling and simulation simulation-based optimization OptQuest

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A socio-technical exploration of the Car as Power Plant

A socio-technical exploration of the Car as Power Plant

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作者： Esther Hae-Kyung PARK LEE Delft University of Technology

学位级别：博士

Introduction In the transition towards low-carbon energy systems, the growth of variable renewable energy sources (V-RES) like solar and wind in the electricity systems is calling for more flexibility measures. These are needed to cope with the increased uncertainty and variability that affects the residual demand. Flexibility can be offered by traditional players in the sector, through dispatchable generation, storage, demand response, and increased interconnection. However, there are also increasing opportunities for new actors and roles. Aggregators, for example, can exploit the flexibility of small consumers and trade it on their behalf in the electricity markets. This flexibility can also be provided from other sectors, such as heating and transportation. With the adoption and diffusion of electric vehicles, the aggregated capacity is considered to have significant potential to support the grid in the future. Vehicles are only used 5% of the time for driving. Thus, when parked, they could be used for providing flexibility through storage or providing vehicle-to-grid (V2G) power. The Car as Power Plant (CaPP) concept proposes integrated energy and transport systems based on renewable energy, hydrogen, and Fuel Cell Electric Vehicles (FCEVs). In this concept, hydrogen is used for storage of renewable electricity, for transportation and re-electrification. Parked FCEVs can be used to provide flexible electricity through V2G. In this context, vehicle owners and drivers become prosumers in the electricity system. From a socio-technical systems view, the availability of FCEVs for V2G is not only constrained by the drivers' driving needs, but also their willingness to participate. Prosumers, with their different actions and participation preferences, have to be considered when analyzing the feasibility of the vehicle-to-grid concept. More importantly, the rules needed for managing these V2G transactions have to be defined. This research explored the operation of fuel

关键词： vehicle-to-grid contracts fuel cell electric vehicles socio-technical systems agent-based modeling and simulation

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agent-based evacuation modeling with multiple exits using NeuroEvolution of Augmenting Topologies

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ADVANCED ENGINEERING INFORMATICS 2018年 35卷 30-55页

作者： Yuksel, Mehmet Erkan Mehmet Akif Ersoy Univ Dept Comp Engn Burdur Turkey

Evacuation modeling offers challenging research topics to solve problems related to the development of emergency planning strategies. In this paper, we built an agent-based evacuation simulation model to study the pedestrian dynamics and learning process by applying the NeuroEvolution of Augmenting Topologies (NEAT) which is a powerful method to evolve artificial neural networks (ANNs) through genetic algorithms (GAs). The NEAT method strengthens the analogy between GAs and biological evolution by both optimizing and complexifying the solutions simultaneously. We set our main goal to develop a model by identifying the most appropriate fitness function for the agents that can learn how to change and improve their behaviors in a simulation environment such as moving towards the visible targets, producing efficient locomotion, communicating with each other, and avoiding obstacles while reaching targets. The fitness function we chose captured the learning process effectively and our NEAT-based implementation evolved suitable structures for the ANNs autonomously. According to our experiments and observations in the simulated environment, the agents accomplished their tasks successfully and found their ways to the exits.

关键词： Evolutionary computation Neuroevolution Genetic algorithms agent-based modeling and simulation Evacuation modeling Emergency evacuation

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simulation study on opinion formation models of heterogeneous agents based on game theory and complex networks

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simulation-TRANSACTIONS OF THE SOCIETY FOR modeling AND simulation INTERNATIONAL 2017年第11期93卷 899-919页

作者： Li, Ying Cao, Hongduo Wen, Genfeng Sun Yat Sen Univ Sch Business Guangzhou 510275 Guangdong Peoples R China

This study investigates a new opinion formation model of heterogeneous agents, a network stubborn individuals and orators (NSO) model based on game theory and complex social networks. Game theory solves economists' rational choice-making problems, and complex social networks reflect the social impact on opinion evolution. The NSO model involves both social and individual heterogeneous characteristics. In a society, the more unequal the members, and the closer the social distances, the faster opinions spread. In the real world, the power-law degree distribution and the short paths in social networks can generate the rapid spread of an opinion. This study also investigates opinion control under the NSO model. The results show that opinion guidance is most likely to separate the public into different groups rather than converge to the guide's opinion.

关键词： Opinion dynamics game theory complex network agent-based modeling and simulation network stubborn individuals and orators (NSO) model opinion guide

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agent-based modeling of Society Resistance against Unpopular Norms

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INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS 2019年第2期43卷 209-219页

作者： Zia, Kashif Saini, Dinesh Kumar Muhammad, Arshad Farooq, Umar Sohar Univ Fac Comp & Informat Technol Sohar Oman Univ Sci & Technol Bannu Khyber Pakhtunkhwa Pakistan

People lives in a society adhering to different types of norms, and some of these norms are unpopular. This paper proposes an agent-based model for unpopular norm aversion. The proposed model is simulated asking important "what-if' questions to elaborate on the conditions and reasons behind the emergence, spreading and aversion of unpopular norms. Such conditions can thus be analyzed and mapped onto the behavioral progression of real people and patterns of their interactions to achieve improved societal traits particularly using the new social landscape dominated by digital content and social networking. Hence, it can be argued that careful amalgamation of social media content can not only educate the people but also help them in an aversion of undesirable behaviors such as retention and spreading of unpopular norms. simulation results revealed that to achieve a dominant norm aversion, an agent population must incorporate a rational model, besides, active participation of agents in averting unpopular norms.

关键词： agent-based modeling and simulation unpopular norms emperor's dilemma norm aversion

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Integrating Machine Learning With Microsimulation to Classify Hypothetical, Novel Patients for Predicting Pregabalin Treatment Response based on Observational and Randomized Data in Patients With Painful Diabetic Peripheral Neuropathy

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PRAGMATIC AND OBSERVATIONAL RESEARCH 2019年 10卷 67-76页

作者： Alexander, Joe, Jr. Edwards, Roger A. Manca, Luigi Grugni, Roberto Bonfanti, Gianluca Emir, Birol Whalen, Ed Watt, Steve Brodsky, Marina Parsons, Bruce Pfizer Inc Global Med Affairs New York NY 10017 USA Hlth Serv Consulting Corp 169 Summer Rd Boxboro MA 01719 USA Fair Dynam Consulting SRL Milan Italy Pfizer Inc Global Stat New York NY 10017 USA Pfizer Inc Global Med Affairs Groton CT 06340 USA Pfizer Inc Global Med Prod Evaluat New York NY 10017 USA

Purpose: Variability in patient treatment responses can be a barrier to effective care. Utilization of available patient databases may improve the prediction of treatment responses. We evaluated machine learning methods to predict novel, individual patient responses to pregabalin for painful diabetic peripheral neuropathy, utilizing an agent-based modeling and simulation platform that integrates real-world observational study (OS) data and randomized clinical trial (RCT) data. Patients and methods: The best supervised machine learning methods were selected (through literature review) and combined in a novel way for aligning patients with relevant subgroups that best enable prediction of pregabalin responses. Data were derived from a German OS of pregabalin (N=2642) and nine international RCTs (N=1320). Coarsened exact matching of OS and RCT patients was used and a hierarchical cluster analysis was implemented. We tested which machine learning methods would best align candidate patients with specific clusters that predict their pain scores over time. Cluster alignments would trigger assignments of cluster-specific time-series regressions with lagged variables as inputs in order to simulate "virtual" patients and generate 1000 trajectory variations for given novel patients. Results: Instance-based machine learning methods (k-nearest neighbor, supervised fuzzy c-means) were selected for quantitative analyses. Each method alone correctly classified 56.7% and 39.1% of patients, respectively. An "ensemble method" (combining both methods) correctly classified 98.4% and 95.9% of patients in the training and testing datasets, respectively. Conclusion: An ensemble combination of two instance-based machine learning techniques best accommodated different data types (dichotomous, categorical, continuous) and performed better than either technique alone in assigning novel patients to subgroups for predicting treatment outcomes using microsimulation. Assignment of novel patients t

关键词： coarsened exact matching hierarchical cluster analysis time series regressions agent-based modeling and simulation machine learning

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Formal and computational modeling of anticipation mechanisms of resilience in the complex sociotechnical air transport system

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COMPLEX ADAPTIVE SYSTEMS modeling 2018年第1期6卷 1页

作者： Blok, Anne-Nynke Sharpanskykh, Alexei Vert, Matthieu Delft Univ Technol Fac Aerosp Engn Kluyverweg 1 Delft Netherlands ProRail Utrecht Netherlands

With ever-growing numbers of passengers and complexity of the air transport system, it becomes more and more of a challenge to manage the system in an effective, safe, and resilient manner. This is especially evident when disruptions occur. Understanding and improving resilience of the air transport system and its adaptive capacity to disruptions is essential for the system's uninterrupted successful performance. Using theoretical findings from behavioral sciences, this paper makes the first steps towards formalization of the adaptive capacity of resilience of the air transport system with a particular focus on its ability to anticipate. To this end, an expressive logic-based language called Temporal Trace Language is used. The proposed approach is illustrated by a case study, in which anticipatory mechanisms are implemented in an agent-based airport terminal operations model, to deal with a disruptive scenario of unplanned and challenging passenger demand at the security checkpoint. Results showed that the timing of an adaptive action could have a significant influence on reducing the risk of saturation of the system, where saturation implies performance loss. Additionally, trade-off relations were obtained between cost, corresponding to the extra resources mobilized, and the benefits, such as a decrease in risk of saturation of the passenger queue.

关键词： Resilience Anticipation agent-based modeling and simulation Air transport system

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Web-oriented Software System for agent-based modeling Driven by Declarative Specification of Implementation Process 3

Web-oriented Software System for Agent-based Modeling Driven...

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3rd Russian-Pacific Conference on Computer Technology and Applications (RPC)

作者： Nikolaychuk, Olga A. Pavlov, Alexander, I Stolbov, Alexander B. ISDCT SB RAS Lab Informat Technol Study Nat & Technol Secur Irkutsk Russia ISDCT SB RAS Lab Syst Anal & Computat Methods Irkutsk Russia

ISBN: (纸本)9781538675311

The article discusses information models for describing the typical elements and software tools used for development of agent-based simulation models, including the inference and the simulation engine. Step-by-step specification formation method of the agent model driven by the domain ontology is proposed. A web-oriented software system was developed to approbate the method. It is provided implementation of that specification based on an extensible toolkit, for example Jess and Madkit.

关键词： agent-based modeling and simulation model driven development ontology domain expert orientation

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simulation Analysis of Social Norm Formation in Escalator Uses

Simulation Analysis of Social Norm Formation in Escalator Us...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Toda, Myoshi Takahashi, Shingo Waseda Univ Dept Ind & Management Syst Engn Tokyo Japan

ISBN: (纸本)9781538666500

Currently observed escalator usage in Japan is to stand on one side, which is considered as a social norm. Originally, escalator usage in Japan took the form of "standing on both sides." Hence escalator usage norms have changed over time. For mainly safety reasons, efforts have been made to establish standing on both sides as the social norm for escalator usage. The efforts, however, have not been effective as yet and most people still "stand on one side" when they use an escalator. This paper develops an agent-based model to reproduce the current situation observed in escalator usage expressed like in a game for extensive form and to analyze possible causes as to why standing on one side has been established as the current norm based on three hypotheses and finally to examine the effectiveness of measures for changing the current norm.

关键词： social norm escalator usage agent-based modeling and simulation

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