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Journal of Systems Science and Systems Engineering 2021年第1期30卷 85-104页

作者： Jiachen Sun Peter Gloor mit center for collective intelligence 245 First StreetCambridgeMA02142USA School of Electronics and Information Technology Sun Yat-Sen UniversityGuangzhou510275China

Rapid advances in machine learning combined with wide availability of online social media have created considerable research activity in predicting what might be the news of tomorrow based on an analysis of the *** this work,we present a deep learning forecasting framework which is capable to predict tomorrow’s news topics on Twitter and news feeds based on yesterday’s content and topic-interaction *** proposed framework starts by generating topics from words using word embeddings and K-means *** temporal topic-networks are constructed where two topics are linked if the same user has worked on both *** and dynamic metrics calculated from networks along with content features and past activity,are used as input of a long short-term memory(LSTM)model,which predicts the number of mentions of a specific topic on the subsequent *** dependencies among topics,our experiments on two Twitter datasets and the HuffPost news dataset demonstrate that selecting a topic’s historical local neighbors in the topic-network as extra features greatly improves the prediction accuracy and outperforms existing baselines.

关键词： Topic’s popularity trend forecasting social media

Distributed Optimization Algorithm for Multi-Robot Formation with Virtual Reference center

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 732-734页

作者： Jingyi Huang Shuaiyu Zhou Hua Tu Yuhong Yao Qingshan Liu the School of Mathematics Southeast University IEEE the Jiangsu Provincial Key Laboratory of Networked collective intelligence

Dear editor,In this letter,we use a distributed optimization approach to solve a class of multi-robot formation problem with virtual reference *** investigate the design and analysis of the constrained consensus algorithm to solve the optimization problem with a sum of objective functions with some local *** the multi-robot system with virtual reference center,each robot has messages on its own constraints and objective function,as well as the message about the formation that interacts with the virtual reference *** the same time,all the robots collaborate to find the minimum value of the function defined by the *** find the optimal formation,we propose an algorithm with fixed step size with better *** addition,we use a combination of the Hungarian assignment algorithm and the proposed formation algorithm to get the optimal matching formation of the multi-robot system.

关键词： robot Robot editor

A MACHINE LEARNING APPROACH FOR MECHANISM SELECTION IN COMPLEX NEGOTIATIONS

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Journal of Systems Science and Systems Engineering 2018年第2期27卷 134-155页

作者： Reyhan Aydogan Ivan Marsa-Maestre Mark Klein Catholijn M. Jonker Department of Computer Science Ozyegin University Istanbul Turkey reyhan Interactive intelligence Group Delft University of Technology The Netherlands Department of Computer Engineering University of Alcala 28805 Alcala de Henares Madrid Spain ivan Interactive center for collective intelligence Massachusetts Institute of Technology Cambridge USA

Automated negotiation mechanisms can be helpful in contexts where users want to reach mutually satisfactory agreements about issues of shared interest, especially for complex problems with many interdependent issues. A variety of automated negotiation mechanisms have been proposed in the literature. The effectiveness of those mechanisms, however, may depend on the charaeteristics of the underlying negotiation problem （e.g. on the complexity of participant＇s utility functions, as well as the degree of conflict between participants）. While one mechanism may be a good choice for a negotiation problem, it may be a poor choice for another. In this paper, we pursue the problem of selecting the most effective negotiation mechanism given a particular problem by （1） defining a set of scenario metrics to capture the relevant features of negotiation problems, （2） evaluating the performance of a range of negotiation mechanisms on a diverse test suite of negotiation scenarios, （3） applying machine learning techniques to identify which mechanisms work best with which scenarios, and （4） demonstrating that using these classification rules for mechanism selection enables significantly better negotiation performance than any single mechanism alone.

关键词： Automated negotiation mechanism selection scenario metrics

Complex network approach for the evaluation of asphalt pavement design and construction: a longitudinal study

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Science China(Information Sciences) 2022年第7期65卷 210-224页

作者： Hanjie LIU Jinde CAO Wei HUANG Xinli SHI Xudong WANG School of Mathematics Southeast University Jiangsu Provincial Key Laboratory of Networked collective intelligence Southeast University Intelligent Transportation System Research center Southeast University School of Cyber Science and Engineering Southeast University Research Institute of Highway Ministry of Transport

The assessment of asphalt pavement structures with diversified designs and constructions has been a critical challenge due to the practical limitations in testing and methodology. Here, we propose a complex network approach to the evaluation of longitudinal asphalt pavement performances in the Research Institute of Highway Ministry of Transport track(RIOHTrack). We add to the growing field in which network approaches are employed and indicate the profound application in understanding pavement ***, similar and disparate pavement performances are revealed regardless of their predefined design and construction categories. Evidence shows that short-term pavement performance depends on the strength of the subbase structure, whereas long-term performance relies on the thickness of the asphalt layer. In addition, our results indicate that recycling materials could be an important substitute for reducing the thickness of asphalt concrete and maintaining a healthy service life.

关键词： complex network asphalt pavement structure evaluation longitudinal RIOHTrack

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ARISTOTLE SAID ＂HAPPINESS IS A STATE OF ACTIVITY＂ - PREDICTING MOOD THROUGH BODY SENSING WITH SMARTWATCHES

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Journal of Systems Science and Systems Engineering 2018年第5期27卷 586-612页

作者： Peter A Gloor Andrea Fronzetti Colladon Francesca Grippa Pascal Budner Joscha Eirich mit center for collective intelligence 245 First Street 02142 Cambridge MA USA Department of Enterprise Engineering University of Rome Tor Vergata Via del Politecnico n°1 00133 Rome Italy Northeastern University 360 Huntington Avenue 02115 Boston MA USA University of Cologne Albertus-Magnus-PIatz 50923 Koln Germany University of Bamberg Kapuzinerstraβe1696047 Bamberg Germany

We measure and predict states of Activation and Happiness using a body sensing applicationconnected to smartwatches. Through the sensors of commercially available smartwatches we collectindividual mood states and correlate them with body sensing data such as acceleration, heart rate, lightlevel data, and location, through the GPS sensor built into the smartphone connected to the smartwatchWe polled users on the smartwatch for seven weeks four times per day asking for their mood state. Wefound that both Happiness and Activation are negatively correlated with heart beats and with the levelsof light. People tend to be happier when they are moving more intensely and are feeling less activatedduring weekends. We also found that people with a lower Conscientiousness and Neuroticism andhigher Agreeableness tend to be happy more frequently. In addition, more Activation can be predictedby lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find thattracking people＇s geographical coordinates might play an important role in predicting Happiness andActivation. The methodology we propose is a first step towards building an automated mood trackingsystem, to be used for better teamwork and in combination with social network analysis studies.

关键词： Body sensing systems mood tracking smartwatch experience sampling happiness activation

Research on the basic theoretical issues of smart metro construction

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Science China(Technological Sciences) 2019年第11期62卷 2038-2051页

作者： WEI Yun HUANG Wei CAO JinDe BAI WenFei TONG ShuZhen National Engineering Laboratory for Green&Safe Construction Technology in Urban Rail Transit Beijing 10037China Beijing Urban Construction Design&Development Group Co. LimitedBeijing 100037China Jiangsu Provincial Key Laboratory of Networked collective intelligence ITS Research CenterSoutheast UniversityNanjing 210096China

The basic conception and theoretical system of smart metro are not clear and there is not a unified understanding at the academic *** on this fact,there is no guidance of the smart metro ***,this paper conducts a complete and systemic research on several basic theoretical issues of smart metro,such as the development history,concept,connotation,characteristics,evolution stages,system architecture and main construction ***,the internal and external development demands are analyzed in this *** addition,the subject-cycle-function(SCF)model of smart metro concept is ***,the essential connotation,three typical characteristics and the evolution process of smart metro are ***,the evolution relationships of main function,achievement goal,instrument subject,decision subject,control subject and factor relationship for every evolution stage are ***,according to the theory of system engineering,the three-hierarchy system architecture and five main construction contents are *** both can be used to construct the technical system of smart metro at the academic level,and provide theoretical support and technical guidance for promoting the development of smart metro construction in China.

关键词： smart metro basic theory issues system architecture

Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track

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Science China(Information Sciences) 2023年第5期66卷 196-214页

作者： Yu WANG Jiaojiao YAN Wei HUANG Leszek RUTKOWSKI Jinde CAO School of Mathematics Southeast University Jiangsu Provincial Key Laboratory of Networked collective intelligence Southeast University Intelligent Transportation System Research center Southeast University Systems Research Institute of the Polish Academy of Sciences Institute of Computer Science AGH University of Science and Technology Information Technology Institute University of Social Sciences Yonsei Frontier Lab Yonsei University

Rutting deformation is typical damage to asphalt pavement and can be quantitatively described as the time-varying mechanical deformation feature of the asphalt mixture during the creep process. First,a nonlinear viscoelastic creep model is established based on the Caputo variable-order fractional *** fractional order in this model is not fixed and is defined as a time-varying function. The time-dependent mechanical properties of asphalt mixtures are efectively reflected. Based on the modified Burgers model, the variable-order function is revised to a linear form. Second, the variable-order fractional Burgers rutting model is obtained by fitting the test data of the RIOHTrack full-scale track. The Levenberg-Marquardt optimization algorithm is used to analyze the test data and the corresponding parameters to obtain more accurate and applicable variable-order fractional rutting mechanics and empirical models for diferent asphalt pavement structures. Finally, according to the classification of the pavement structure, structures III and VI are taken as examples. The rutting prediction and comparison results of several representative pavement structures are obtained to verify that the proposed rutting prediction model can also accurately predict all road sections of RIOHTrack. The new model is also compared with the rutting model of the mechanistic-empirical pavement design guide, the fractional-order Burgers rutting model, and the modified Burgers rutting model. The fitting results are evaluated using the determination coefficient R2. The results show that the variable-order fractional Burgers rutting model proposed in this study exhibits a better fit and is more applicable to describe the rutting deformation of asphalt pavement.

关键词： RIOHTrack full-scale track Caputo fractional derivative variable-order fractional modified Burgers model rutting prediction

DeepTSP:Deep traffic state prediction model based on large-scale empirical data

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Communications in Transportation Research 2021年第1期1卷 90-99页

作者： Yang Liu Cheng Lyu Yuan Zhang Zhiyuan Liu Wenwu Yu Xiaobo Qu Department of Architecture and Civil Engineering Chalmers University of TechnologyGothenburgSweden Jiangsu Key Laboratory of Urban ITS Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic TechnologiesSchool of TransportationSoutheast UniversityChina Jiangsu Provincial Key Laboratory of Networked collective intelligence School of MathematicsSoutheast UniversityNanjingChina

Real-time traffic state(e.g.,speed)prediction is an essential component for traffic control and management in an urban road *** to build an effective large-scale traffic state prediction system is a challenging but highly valuable *** study focuses on the construction of an effective solution designed for spatiotemporal data to predict the traffic state of large-scale traffic *** this study,we first summarize the three challenges faced by large-scale traffic state prediction,i.e.,scale,granularity,and *** on the domain knowledge of traffic engineering,the propagation of traffic states along the road network is theoretically analyzed,which are elaborated in aspects of the temporal and spatial propagation of traffic state,traffic state experience replay,and multi-source data fusion.A deep learning architecture,termed as Deep Traffic State Prediction(DeepTSP),is therefore proposed to address the current challenges in traffic state *** demonstrate that the proposed DeepTSP model can effectively predict large-scale traffic states.

关键词： Large-scale traffic prediction Traffic state propagation Spatio-temporal data

Distributed online bandit tracking for Nash equilibrium under partial-decision information setting

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Science China(Technological Sciences) 2023年第11期66卷 3129-3138页

作者： FENG ZhangCheng XU WenYing CAO JinDe YANG ShaoFu RUTKOWSKI Leszek Jiangsu Provincial Key Laboratory of Networked collective intelligence School of MathematicsSoutheast UniversityNanjing 211189China Frontiers Science center for Mobile Information Communication and Security Nanjing 210096China School of Computer Science and Engineering Southeast UniversityNanjing 211189China The Systems Research Institute of the Polish Academy of Sciences Warsaw 01-447Poland AGH University of Science and Technology Krakow 30-059Poland

This paper is concerned with a Nash equilibrium(NE)tracking issue in online games with bandit feedback,where cost functions vary with time and agents only have access to the values of these functions at two points during each round.A partial-decision information setting is considered,in which agents have only access to the decisions of their *** primary objective of this paper is to develop a distributed online NE tracking algorithm that ensures sublinear growth of regret with respect to the total round T,under both the bandit feedback and partial-decision information *** utilizing a two-point estimator together with the leader-following consensus method,a new distributed online NE tracking algorithm is established with the estimated gradient and local estimated decisions based on the projection gradient-descent ***,sufficient conditions are derived to guarantee an improved upper bound of dynamic regret compared to existing bandit ***,a simulation example is presented to demonstrate the effectiveness of the proposed algorithm.

关键词： online game bandit feedback partial-decision two-point gradient estimator

CONSENSUS FORMATION OF TWO-LEVEL OPINION DYNAMICS

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Acta Mathematica Scientia 2014年第4期34卷 1029-1040页

作者： Yilun SHANG SUTD-mit International Design center Singapore University of Technology and Design20 Dover Drive138682Singapore

Opinion dynamics have received significant attention in recent years. This paper proposes a bounded confidence opinion model for a group of agents with two different confidence levels. Each agent in the population is endowed with a confidence interval around her opinion wiih radius αd or （1 - α）d, where α∈ （0, 1/2] represents the differentiation of confidence levels. We analytically derived the critical confidence bound dc = 1/（4α） for the two-level opinion dynamics on Z. A single opinion cluster is formed with probability 1 above this critical value regardless of the ratio p of agents with high/low confidence. Extensive numerical simulations are performed to illustrate our theoretical results. Noticed is a clear impact of p on the collective behavior： more agents with high confidence lead to harder agreement. It is also experimentally revealed that the sharpness of the threshold dc increases with a but does not depend on p.

关键词： social dynamics bounded confidence phase transition Monte Carlo simulation