Neural Computing and Applications

Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the effects of TIC on conflict resolution by conducting ...

In this paper, we study and analyse the teaching video of oil painting art through machine learning combined with virtual reality computing. Since the current oil painting, image acquisition method cannot meet the user's demand for multi-...

The development of smart city is of strategic significance to the realization of modern society in China, and rail transit network is an important part of urban development. Currently, China's urban rail transport is at the bottleneck stage, and ...

At present, the mortgage loan of farmland contractual management right is in the pilot and exploration stage. In this overall environment, how to formulate an appropriate pricing model according to the particularity of farmland property right and ...

This paper proposed a two-stage Voxel-based 3D Object detector which named GVnet. Voxel-based method mainly relies on sampling and Grouping point in voxel and the feature map generated by subsequent 3D CNN to control the quality of detection. ...

The quality of anesthesia is of great value to the risk of surgery and the recovery of postoperative patients. The evaluation of depth of anesthesia through EEG signals is an effective method to improve the quality of anesthesia. The difficulty of ...

Convolutional neural networks also encountered some problems in the development of image recognition. The most prominent problem is that it is costly and time-consuming to collect data sets and train models. Limited data sets will cause the ...

Under the impact of agricultural industry differentiation, traditional financial risk model cannot forewarn the guarantee risk of agricultural credit with effectively. This paper proposes an early warning algorithm of agricultural credit and ...

In the grasping process of the robot, the pose of robot should adapt to the change of the object's pose. In order to avoid the cumbersome calibration and difficulty of inversion in the existing vision-based robotic arm-grasping methods, a robotic ...

Urban economic development is not linear, but it always exhibits certain volatility. If the economic fluctuation exceeds a certain range, it may damage the urban economic development. In order to solve the economic damage caused by the excessive ...

Due to safety issues when passengers get on and off the subway and spend a lot of time on the subway, this makes subway station signs very important. Moreover, in case of fire and other dangerous situations and emergency evacuation, the guiding ...

This paper investigates the art design of user interaction experience in mobile systems through the methods of contextual perception and machine learning. The theoretical foundations for the design of intangible cultural heritage interactive ...

Hepatic fibrosis is the body’s response to chronic liver disorders caused by various causes. Ultrasonic examination using an intelligent algorithm is increasingly important for the diagnosis of hepatic fibrosis. The purpose of this study was to ...

With the development of science and technology and the progress of the times, robots have slowly entered people's lives and work. However, how to control robots to bypass obstacles has become the focus of current research. Different from other ...

E-commerce platforms apply recommendation technology to a wide variety of commercial websites to help users quickly find the product they need from a large number of products. At present, recommendation systems have been widely used in large-scale ...

Coronary heart disease is a heart disease caused by coronary atherosclerosis, which seriously endangers human life and health. More and more studies have shown that diabetes is one of the main pathogenic factors of coronary heart disease and has ...

The traditional dance training process lacks a certain degree of scientificity due to the lack of precise motion capture and analysis system, which directly affects the final training effect. In view of the robust limitations of the type 1 fuzzy ...

Traditional navigation systems rely mainly on satellite navigation, but internal positioning and navigation cannot be achieved. This is mainly due to the inability to penetrate the wall due to the complex internal environment and the signal ...

Target recognition difficulty quantification and prediction using the search time for the human visual system to target an object is a challenging task, which can effectively guide the training of machine learning models such as target recognition ...

Learning automata (LA), a powerful tool for reinforcement learning in the field of machine learning, could explore its optimal state by continuously interacting with an external environment. Generally, the traditional LA algorithms, especially ...

Stochastic Point Location problem considering that a learning entity (i.e. mechanisms, algorithm, etc) attempts to locate a certain point by interaction with a stochastic environment is encountered widely in Machine Learning. A conventional ...

Learning using privileged information (LUPI) paradigm, which pioneered teacher–student interaction mechanism, makes the learning models use additional information in the training stage. This paper is the first to propose an incremental learning ...

Indoor scene recognition is a growing field with great potential for behaviour understanding, robot localization, and elderly monitoring, among others. In this study, we approach the task of scene recognition from a novel standpoint, using multi-...

We develop a deep learning architecture for inverse design of a self-oscillating sheet propelled by an embedded chemical reaction. The dynamics of our problems are nonlinear and exhibit chaotic behavior, a challenging setting for existing deep-...

The double-row layout problem (DRLP) was previously investigated as an unconstrained optimisation problem without enforcing any limits on the arrangement of the machines. However, in reality, a DRLP is required to respect certain facility ...

Inspired by the massive surge of interest in the Internet of Things (IoT), this work focuses on the kinetics of its security. By automating everything, starting from baby monitors to life-saving medical devices, IoT brought convenience to people’s ...

Recently, many outstanding techniques for Time series forecasting (TSF) have been proposed. These techniques depend on necessary and sufficient data samples, which is the key to train a good predictor. Thus, an Active learning (AL) algorithmic ...

Nowadays, artificial neural networks (ANN) are models widely used in many areas; one of these is the classification of urban areas. This work aims to discuss a new framework for the delimitation of functional zones for the city of Naples through ...

In recent years, the ever-growing contents (movies, clothes, books, etc.) accessible and buyable via the Internet have led to the information overload issue and therefore the item targeting problem. Indeed, the huge mass of contents complexifies ...