Yang H.Yao Y.Qi H.Guo M....
5页查看更多>>摘要：© 2022 Elsevier B.V.Most of the safety studies mainly takes the probability of crashes or relevant records as the main indicators. Accident-based safety analysis may lead to overestimation or underestimation of traffic risks, which are delayed and sparse. Aggressive driving behavior is one of the major causes of traffic accidents, which can accurately measure traffic risk, but is not widely adopted due to limitations in data collection. This paper took the Traffic Order Index (TOI) as the surrogate index of safety risk based on aggressive driving behavior and speed variation and developed the Multinomial Logistic Regression (MLR) and the Random Forest (RF) model to identify risk level on bridge sections of freeway, which can minimize the restrictions of crash occurrence or crash-related data in discovering contributing factors of traffic risks. The results revealed that the RF has a better performance than MLR in the performance comparison of the two classifiers. The feature importance based on the Gini coefficient was used to identify the most influential variable of identified results of risk. The top four ranked variables that significantly affect the identified results of traffic order level are congestion index, road section types, the level of the number of users, and weather. In addition, the partial dependency plots of the explanatory variables are presented to reveal interactions between different variable types on traffic risks. Finally, the conclusion based on the traffic order level analysis has basically corresponded to the accident analysis. Identification of these specific risk prone conditions could improve our understanding of traffic risk and would shed light on countermeasures for improving the safety of bridge sections of freeways.
原文链接:
NSTL
Cai S.-M.Zhou T.Zhao Z.-D.Nie W.-P....
5页查看更多>>摘要：© 2022 Elsevier B.V.Taxi movements contain much mobility information of passengers and taxi drivers in a city. However, previous researches often overlook the continuous movements of a single taxi. In this paper, we study the mobility pattern of taxi movements by analyzing the visiting sequences which record the cells (i.e., locations) being visited by taxis. At the collective level, we observe the weak power-law scaling exists in the relation between the number of visits of a cell and the corresponding number of taxis. At the individual level, we notice some unusual characteristics of continuous movements of a single taxi: (i) the number of different cells that have been visited increase with the visit number and shows a robust scaling behavior; (ii) the cell's visiting frequency decreases with the rank of the cell and presents as a logarithm function; (iii) The distribution of the number of visits taken to revisit one cell presents as an exponential distribution. The empirical result demonstrates that the taxi movements do follow the unified pattern and show a stronger exploration tendency and weaker preferential return than other human dynamics. Finally, we utilize an agent-based model to reveal and understand the unified pattern of taxi movements. The model results indicate that the rank distribution is an intrinsic characteristic to explore the taxi destination choice and simulate the taxi movements.
原文链接:- NSTL
Lopez Perez M.Mansilla Corona R.
5页查看更多>>摘要：© 2022 Elsevier B.V.In this paper we study Algorithmic High-Frequency Financial Markets as dynamical networks. After an individual analysis of 24 stocks of the US market during a trading year of fully automated transactions by means of ordinal pattern series, we define an information-theoretic measure of pairwise synchronization for time series which allows us to study this subset of the US market as a dynamical network. We apply to the resulting network a couple of clustering algorithms in order to detect collective market states, characterized by their degree of centralized or decentralized synchronicity. This collective analysis has shown to reproduce, classify and explain the anomalous behavior previously observed at the individual level. We also find two whole coherent seasons of highly centralized and decentralized synchronicity, respectively. Finally, we model these states dynamics through a simple Markov model.
原文链接:- NSTL
Xu D.Qian Y.Da C.Zeng J....
5页查看更多>>摘要：© 2022 Elsevier B.V.In this paper, a bidirectional quasi-moving block cellular automaton model for single-track railways is proposed to simulate the impact of quasi-moving block on the passing capacity of single track railway. The rules of train departure, meeting, entering the station and running in the section are formulated and the Naqu–Lhasa section of the Qinghai–Tibet Railway is taken as an example for simulation. The results show that, under the quasi moving block, with the changes of the mixed ratio and stop time of freight train, the passing capacity is improved compared with the currently adopted automatic inter-station block. Besides, it is found that the passing capacity is the largest under equal station spacing conditions, indicating that the distance between stations should be minimized in the preliminary line design.
原文链接:- NSTL
Yukalov V.I.Yukalova E.P.Sornette D.
5页查看更多>>摘要：© 2022 Elsevier B.V.A network of agents is considered whose decision processes are described by the quantum decision theory previously advanced by the authors. Decision making is done by evaluating the utility of alternatives, their attractiveness, and the available information, whose combinations form the probabilities to choose a given alternative. As a result of the interplay between these three contributions, the process of choice between several alternatives is multimodal. The agents interact by exchanging information, which can take two forms: information that an agent can directly receive from another agent and information collectively created by the members of the society. The information field common to all agents tends to smooth out sharp variations in the temporal behaviour of the probabilities and can even remove them. For agents with short-term memory, the probabilities often tend to their limiting values through strong oscillations and, for a range of parameters, these oscillations last for ever, representing an ever lasting hesitation of decision makers. Switching on the information field makes the amplitude of the oscillations smaller and even halt the oscillations forcing the probabilities to converge to fixed limits. The dynamic disjunction effect is described.
原文链接:- NSTL
da Fontoura Costa L.Silva F.N.Amancio D.R.Ferraz de Arruda H....
5页查看更多>>摘要：© 2022 Elsevier B.V.Poetry and prose are written artistic expressions that help us appreciate the reality we live in. Each of these styles has its own set of subjective properties, such as rhyme and rhythm, which are easily caught by a human reader's eye and ear. With the recent advances in artificial intelligence, the gap between humans and machines may have decreased, and today we observe algorithms mastering tasks that were once exclusively performed by humans. In this paper, we propose a computational method to distinguish between poetry and prose based solely on aural and rhythmic properties. In order to compare prose and poetry rhythms, we represent the rhymes and phonemes as temporal sequences, and thus, we propose a procedure for extracting rhythmic features from these sequences. The performance of this procedure is evaluated by the use of popular machine learning classifiers, and the best accuracy was obtained with a multilayer perceptron neural network. Interestingly, by using an approach based on complex networks to visualize the similarities between the different texts considered, we found that the patterns of poetry vary more than prose. Consequently, a richer and more complex set of rhythmic possibilities tends to be found in that modality.
原文链接:- NSTL
