Many historical people were only ever captured by old, faded, black and white photos, that are distorted due to the limitations of early cameras passage time. This paper simulates traveling back in time with a modern camera rephotograph famous subjects. Unlike conventional image restoration filters which apply independent operations like denoising, colorization, superresolution, we leverage Sty...

The existing artificial intelligence model uses single-point logging data as the eigenvalue to predict shear wave travel times (DTS), which does not consider longitudinal continuity of along reservoir and lacks multiwell processing method. Low prediction accuracy time affects elastic parameters results in inaccurate sand production prediction. This paper establishes based on standardization, no...

Due to the increasing traffic volume in metropolitan areas, short-term travel time prediction (TTP) can be an important and useful tool for both travelers management. Accurate reliable greatly help vehicle routing congestion mitigation. One of most challenging tasks TTP is developing selecting appropriate algorithm using available data. In this study, data was provided collected from Regional I...

A number of studies have been initiated in the past to address the bus arrival time prediction problem. These efforts have resulted in three types of prediction models: (a) models based on historical data, (b) multilinear regression models, and (c) artificial neural network models. The first type of prediction models infers the current and future travel time of a bus based on the historical tra...

Traffic congestion is becoming a serious environmental threat that must be resolved quickly. Traditionally, travel information systems have been specific to a particular mode of transport. For instance, traffic information (road conditions broadcast) has been directed at drivers. Instead, travel information systems are now being developed which incorporate route guidance systems to divert drive...

Travel time is one of the most critical parameters in proactive traffic management and deployment advanced traveler information systems. This paper proposes a hybrid model named LSTM-CNN for predicting travel highways by integrating long short-term memory (LSTM) convolutional neural networks (CNNs) with attention mechanism residual network. The highway divided into multiple segments considering...

While determining the travel time between stations, a number of design parameters such as waiting time, motion resistance, slope, curve, traction force, maximum speed, vehicle mass, and distance two stations are taken into consideration. These form infrastructure system definition vehicle. Furthermore, while creating speed profile, special attention should be paid to in order ensure defined hea...