Traffic state evaluation is a basic and critical work in the research on road traffic congestion. It can provide data support for improvement measures information release management service. The aim of this to obtain comprehensive value describe accurately based index system. In paper, it carried out using fuzzy c-means (FCM) algorithm entropy weight method. framework, flow was classified into six different states determine range indices improved FCM clustering analysis. Besides, method...

Space–time correlation analysis has become a basic and critical work in the research on road traffic congestion. It plays an important role improving management quality. The aim of this is to examine space–time networks determine likely requirements for building suitable model. In paper, it carried out using flow data collected Beijing’s network. framework, autocorrelation function (ST-ACF) introduced as global measure, cross-correlation (CCF) local measure reveal change mechanism...

Recent research has witnessed the fostered application of machine learning approaches in analyzing single nucleotide polymorphisms (SNP) data, which been proved to be implicated complex human diseases. In identification SNPs responsible for diseases, most genome-wide association studies always took SNP into consideration at one time and ignored diverse interactions between SNPs. One major problems is higher number features relatively small individuals, complicates task harms predictive...

Abstract With the rapid development of metro systems, it has become increasingly important to study phenomena such as passenger flow distribution and boarding behavior. It is difficult for existing methods accurately describe actual situations extend whole system due limitations from parameter uncertainties in their mathematical models. In this article, we propose a passenger‐to‐train assignment model evaluate probabilities individual passengers each feasible train both no‐transfer...

Spatiotemporal information on individual trajectories in urban rail transit is important for operational strategy adjustment, personalized recommendation, and emergency command decision-making. However, due to the lack of journey observations, it difficult accurately infer unknown from based only AFC AVL data. To address problem, this paper proposes a spatiotemporal probabilistic graphical model adaptive expectation maximization attention (STPGM-AEMA) achieve reconstruction trajectories. The...

To achieve vibration isolation across the entire working frequency range, this paper proposes a novel hybrid isolator combining metal rubber and piezoelectric actuators, along with an adaptive active control algorithm. The passive system allows for manual adjustment of stiffness damping based on preload, overcoming issue fixed in traditional units. For system, improved Filtered-x Normalized Least Mean Squares step size algorithm is proposed, problem narrow range applicability algorithms. A...

A compressed sensing radar detection scheme for closing vehicle is proposed in this paper. Because most of the man-made signals are cyclostationary, cyclic autocorrelation domain target return signal sparse. The paper designed based on sparsity signal. From measurements autocorrelation, actual can be reconstructed. simulation, dissertation made that a very simple OMP algorithm get high probability detection.

Compared with conventional travel data such as GPS data, detector and float car call detail record from the cell phone communication not only cost low but also has a large scale which demonstrate it is best way to collect information for studying macroscopic activities. This paper presents complete method discover hot path feature in traffic network by clustering trajectory was acquired signaling data. It valuable planning, public transportation management, monitoring.

With the fast development of metro systems in many big cities, it is important to study characteristics passenger flows based on data for management guarantee service quality and safety. In this article, we build statistical models passengers’ tap-in tap-out times both no-transfer one-transfer cases, propose a Bayesian approach estimate parameters models. These estimators can be used evaluate number measures, which describe degrees congestion comfort, quantify their uncertainties....

This paper addresses the problem of joint optimization subchannel selection and spectrum sensing time for multiband cognitive radio networks. In particular, we construct a framework, derive probabilities detection false alarm taking different gain into account. Furthermore, formulate as two-parameter develop semi--analytical scheme to achieve optimal solution.

Aiming at the transport of biological samples under low temperature environment, a sample robot based on visual SLAM navigation was designed to complete tubes cold storage environment. uses RGB-D three-thread scheme real-time localization and mapping. The algorithm is improved considering that actual environment static stability sufficient illumination, front-end odometer prone mismatching data association time. An "FAST-BRIEF-COUPLING" loosely coupled strategy proposed provide more response...

Accurate information about the vehicle state such as sideslip angle is critical for both advanced assisted driving systems and driverless driving. These states are used active safety control motion planning of vehicle. Since these parameters cannot be directly measured by onboard sensors, this paper proposes an adaptive estimation scheme in case unknown measurement noise. Firstly, method based on bicycle model established using a square-root cubature Kalman filter (SQCKF), secondly,...

This paper utilizes the optimized composite neural network (OCNN)-Hammerstein model to directly identify dynamic inverse hysteresis effect, employing it as a feedforward controller compensate for rate-dependent and amplitude-dependent of piezoelectric actuator. The OCNN-Hammerstein consists an auto-regressive exogenous in series. OCNN comprises convolutional layer radial basis function layer, with its hyperparameters using modified grey wolf optimizer algorithm. Compared existing...

A new method is proposed to solve the problem of image restoration high resolution TDICCD camera due satellite vibrations, which considers blur and irregular sampling geometric quality degradation simultaneously. Firstly, process analyzed according imaging characteristics camera, owing motions during integration time induced by vibrations. In addition, vibration simulation model established, mathematically modeled using bicubic Hermite interpolation. Subsequently, a full developed combined...

We propose an in-orbit modulation transfer function (MTF) statistical estimation algorithm based on natural scene, called SeMTF. The can estimate the MTF of a sensor from image without specialized targets. First, power spectrum satellite is analyzed, then two-dimensional (2-D) fractal Brownian motion model adopted to represent scene. modeled by parametric exponential function. Subsequently, imaging established. Second, solved improved profile-likelihood method. In order handle nuisance...

Deconvolution is a key operation for the post-processing of ultra-wideband (UWB) channel modeling. Due to wideband radio sounding pulse, nature UWB can be frequency selective. This paper presents multi-template compressed sensing (CS) based high-resolution deconvolution algorithm time-domain modeling, considering pulse distortion. channels are prime example long and sparse impulse response (CIR). Furthermore, design dictionary parameterized waveforms that closely matches waveform multipath...