New algorithms for computing the time-to-collision in freeway traffic simulation models.

Abstract:

:Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored which use a two-dimensional coordinate system to track the vehicle trajectories and assess conflicts. Vector-based kinematic variables are used to support the calculations. Algorithms based on boxes, circles, and ellipses are considered. Their performance is evaluated in the context of computational complexity and solution time. Results from these analyses suggest promise for effective and efficient analyses. A combined computation process is found to be very effective.

journal_name

Comput Intell Neurosci

authors

Hou J,List GF,Guo X

doi

10.1155/2014/761047

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

761047

eissn

1687-5265

issn

1687-5273

journal_volume

2014

pub_type

杂志文章
  • Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

    abstract::Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devices. To this end, a technological effort is required to develop neura...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/359590

    authors: Breschi GL,Ciliberto C,Nieus T,Rosasco L,Taverna S,Chiappalone M,Pasquale V

    更新日期:2015-01-01 00:00:00

  • Context Attention Heterogeneous Network Embedding.

    abstract::Network embedding (NE), which maps nodes into a low-dimensional latent Euclidean space to represent effective features of each node in the network, has obtained considerable attention in recent years. Many popular NE methods, such as DeepWalk, Node2vec, and LINE, are capable of handling homogeneous networks. However, ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8106073

    authors: Zhuo W,Zhan Q,Liu Y,Xie Z,Lu J

    更新日期:2019-08-21 00:00:00

  • Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image.

    abstract::This paper brings forth a learning-based visual saliency model method for detecting diagnostic diabetic macular edema (DME) regions of interest (RoIs) in retinal image. The method introduces the cognitive process of visual selection of relevant regions that arises during an ophthalmologist's image examination. To reco...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/7496735

    authors: Zou X,Zhao X,Yang Y,Li N

    更新日期:2016-01-01 00:00:00

  • The Brainarium: An Interactive Immersive Tool for Brain Education, Art, and Neurotherapy.

    abstract::Recent theoretical and technological advances in neuroimaging techniques now allow brain electrical activity to be recorded using affordable and user-friendly equipment for nonscientist end-users. An increasing number of educators and artists have begun using electroencephalogram (EEG) to control multimedia and live a...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/4204385

    authors: Grandchamp R,Delorme A

    更新日期:2016-01-01 00:00:00

  • Liraglutide Activates the Nrf2/HO-1 Antioxidant Pathway and Protects Brain Nerve Cells against Cerebral Ischemia in Diabetic Rats.

    abstract::This study aimed to determine the effect of liraglutide pretreatment and to elucidate the mechanism of nuclear factor erythroid 2-related factor (Nrf2)/heme oxygenase-1 (HO-1) signaling after focal cerebral ischemia injury in diabetic rats model. Adult male Sprague-Dawley rats were randomly divided into the sham-opera...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/3094504

    authors: Deng C,Cao J,Han J,Li J,Li Z,Shi N,He J

    更新日期:2018-02-12 00:00:00

  • Random bin for analyzing neuron spike trains.

    abstract::When analyzing neuron spike trains, it is always the problem of how to set the time bin. Bin width affects much to analyzed results of such as periodicity of the spike trains. Many approaches have been proposed to determine the bin setting. However, these bins are fixed through the analysis. In this paper, we propose ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/153496

    authors: Tamura S,Miyoshi T,Sawai H,Mizuno-Matsumoto Y

    更新日期:2012-01-01 00:00:00

  • Augmenting weak semantic cognitive maps with an "abstractness" dimension.

    abstract::The emergent consensus on dimensional models of sentiment, appraisal, emotions, and values is on the semantics of the principal dimensions, typically interpreted as valence, arousal, and dominance. The notion of weak semantic maps was introduced recently as distribution of representations in abstract spaces that are n...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/308176

    authors: Samsonovich AV,Ascoli GA

    更新日期:2013-01-01 00:00:00

  • The track of brain activity during the observation of TV commercials with the high-resolution EEG technology.

    abstract::We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In partic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2009/652078

    authors: Astolfi L,Vecchiato G,De Vico Fallani F,Salinari S,Cincotti F,Aloise F,Mattia D,Marciani MG,Bianchi L,Soranzo R,Babiloni F

    更新日期:2009-01-01 00:00:00

  • List-Based Simulated Annealing Algorithm for Traveling Salesman Problem.

    abstract::Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/1712630

    authors: Zhan SH,Lin J,Zhang ZJ,Zhong YW

    更新日期:2016-01-01 00:00:00

  • Neural-Based Compensation of Nonlinearities in an Airplane Longitudinal Model with Dynamic-Inversion Control.

    abstract::The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/8575703

    authors: Liu Y,Li Y,Jin F

    更新日期:2017-01-01 00:00:00

  • Robust SAR Automatic Target Recognition Based on Transferred MS-CNN with L2-Regularization.

    abstract::Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via Convolutional Neural Networks (CNNs) has made huge progress toward deep learning, some key issues still remain unsolved due to the lack of sufficient samples and robust model. In this paper, we proposed an efficient transferred Max-Slice CNN ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/9140167

    authors: Zhai Y,Deng W,Xu Y,Ke Q,Gan J,Sun B,Zeng J,Piuri V

    更新日期:2019-11-15 00:00:00

  • Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

    abstract::Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In par...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/971908

    authors: Castelli M,Trujillo L,Vanneschi L

    更新日期:2015-01-01 00:00:00

  • Feature selection with neighborhood entropy-based cooperative game theory.

    abstract::Feature selection plays an important role in machine learning and data mining. In recent years, various feature measurements have been proposed to select significant features from high-dimensional datasets. However, most traditional feature selection methods will ignore some features which have strong classification a...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/479289

    authors: Zeng K,She K,Niu X

    更新日期:2014-01-01 00:00:00

  • An Improved DSA-Based Approach for Multi-AUV Cooperative Search.

    abstract::Multi-AUV cooperative target search problem in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To complete this task, each autonomous underwater vehicle (AUV) needs to move quickly without collision and cooperate with other AUVs to find the target. In this paper, an impro...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2186574

    authors: Ni J,Yang L,Shi P,Luo C

    更新日期:2018-12-02 00:00:00

  • Extracting rhythmic brain activity for brain-computer interfacing through constrained independent component analysis.

    abstract::We propose a technique based on independent component analysis (ICA) with constraints, applied to the rhythmic electroencephalographic (EEG) data recorded from a brain-computer interfacing (BCI) system. ICA is a technique that can decompose the recorded EEG into its underlying independent components and in BCI involvi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/41468

    authors: Wang S,James CJ

    更新日期:2007-01-01 00:00:00

  • Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud Model.

    abstract::The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved. We use an evolutionary algorithm to generate painterly styles of images. Given an input image as the reference target, a cloud model-based evolutionary algorithm that will rerender the target imag...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4518265

    authors: Wu T

    更新日期:2018-02-19 00:00:00

  • Evaluation of a Home Biomonitoring Autonomous Mobile Robot.

    abstract::Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/9845816

    authors: Dorronzoro Zubiete E,Nakahata K,Imamoglu N,Sekine M,Sun G,Gomez I,Yu W

    更新日期:2016-01-01 00:00:00

  • Large-Truck Safety Warning System Based on Lightweight SSD Model.

    abstract::Transportation is an important link in the mining process, and large trucks are one of the important tools for mine transportation. Due to their large size and small driving position, large trucks have a blind spot, which is a hidden danger to the safe transportation of mines and has a great impact on production effic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2180294

    authors: Xiao D,Li H,Liu C,He Q

    更新日期:2019-10-13 00:00:00

  • A Multichannel 2D Convolutional Neural Network Model for Task-Evoked fMRI Data Classification.

    abstract::Deep learning models have been successfully applied to the analysis of various functional MRI data. Convolutional neural networks (CNN), a class of deep neural networks, have been found to excel at extracting local meaningful features based on their shared-weights architecture and space invariance characteristics. In ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/5065214

    authors: Hu J,Kuang Y,Liao B,Cao L,Dong S,Li P

    更新日期:2019-12-31 00:00:00

  • Neurophysiological Responses to Different Product Experiences.

    abstract::It is well known that the evaluation of a product from the shelf considers the simultaneous cerebral and emotional evaluation of the different qualities of the product such as its colour, the eventual images shown, and the envelope's texture (hereafter all included in the term "product experience"). However, the measu...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/9616301

    authors: Modica E,Cartocci G,Rossi D,Martinez Levy AC,Cherubino P,Maglione AG,Di Flumeri G,Mancini M,Montanari M,Perrotta D,Di Feo P,Vozzi A,Ronca V,Aricò P,Babiloni F

    更新日期:2018-09-24 00:00:00

  • A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers.

    abstract::Under the competitive market environment, the game between manufacturers comes down to the competitive multiattribute group decision-making problem. In this study, the evaluation information of experts is given in the form of 2-dimension 2-tuple linguistic variables, and an approach is proposed for the competitive mul...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8389035

    authors: Zhang Q,Jiang K,Yan M,Ma J

    更新日期:2019-11-11 00:00:00

  • Modelling of Asphalt's Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis.

    abstract::The modification by polymers and nanomaterials can significantly improve different properties of asphalt. However, during the service life, the oxidation affects the constituents of modified asphalt and subsequently results in deviation from the desired properties. One of the important properties affected due to oxida...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/3183050

    authors: Arifuzzaman M,Gazder U,Alam MS,Sirin O,Mamun AA

    更新日期:2019-08-15 00:00:00

  • Saliency Mapping Enhanced by Structure Tensor.

    abstract::We propose a novel efficient algorithm for computing visual saliency, which is based on the computation architecture of Itti model. As one of well-known bottom-up visual saliency models, Itti method evaluates three low-level features, color, intensity, and orientation, and then generates multiscale activation maps. Fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/875735

    authors: He Z,Chen X,Sun L

    更新日期:2015-01-01 00:00:00

  • Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

    abstract::Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/4152140

    authors: Shimray BA,Singh KM,Khelchandra T,Mehta RK

    更新日期:2017-01-01 00:00:00

  • Construction Project Safety Performance Management Using Analytic Network Process (ANP) as a Multicriteria Decision-Making (MCDM) Tool.

    abstract::The paper addresses the context in which the construction industry is considered risky, as the intense labor and machine environment interacts with acceleration and overlapping activities. This situation results in accidents and fatalities. A high number of accidents and fatalities leads to additional costs and delays...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/2610306

    authors: Gunduz M,Khader BK

    更新日期:2020-02-25 00:00:00

  • Assessment of Multivariate Neural Time Series by Phase Synchrony Clustering in a Time-Frequency-Topography Representation.

    abstract::Most EEG phase synchrony measures are of bivariate nature. Those that are multivariate focus on producing global indices of the synchronization state of the system. Thus, better descriptions of spatial and temporal local interactions are still in demand. A framework for characterization of phase synchrony relationship...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/2406909

    authors: Porta-Garcia MA,Valdes-Cristerna R,Yanez-Suarez O

    更新日期:2018-03-21 00:00:00

  • SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine.

    abstract::A novel ensemble scheme for extreme learning machine (ELM), named Stochastic Gradient Boosting-based Extreme Learning Machine (SGB-ELM), is proposed in this paper. Instead of incorporating the stochastic gradient boosting method into ELM ensemble procedure primitively, SGB-ELM constructs a sequence of weak ELMs where ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4058403

    authors: Guo H,Wang J,Ao W,He Y

    更新日期:2018-06-26 00:00:00

  • Intelligence Is beyond Learning: A Context-Aware Artificial Intelligent System for Video Understanding.

    abstract::Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to deep feature abstraction, not deep understanding. Deep learning tries to...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8813089

    authors: Ghozia A,Attiya G,Adly E,El-Fishawy N

    更新日期:2020-12-23 00:00:00

  • An Energy Storage Performance Improvement Model for Grid-Connected Wind-Solar Hybrid Energy Storage System.

    abstract::This study introduces a supercapacitor hybrid energy storage system in a wind-solar hybrid power generation system, which can remarkably increase the energy storage capacity and output power of the system. In the specific solution, this study combines the distributed power generation system and the hybrid energy stora...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8887227

    authors: Zhu R,Zhao AL,Wang GC,Xia X,Yang Y

    更新日期:2020-08-28 00:00:00

  • Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting.

    abstract::The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/409361

    authors: Aydin AD,Caliskan Cavdar S

    更新日期:2015-01-01 00:00:00