Neural Computing and Applications

In industrial machinery, rolling bearings are often rated as the most likely to fail in mechanical systems due to excessive working stress. Therefore, effective methods to diagnose the faults in rolling bearings are becoming necessary and required ...

Fuzzy systems are intensively investigated and extended to construct forecasting models. In particular, intuitionistic fuzzy sets are used to capture higher levels of uncertainty occurring in the modeled data. Neural networks are also used to ...

The success of deep learning (DL) in various areas, such as computer vision, fueled the interest in several novel DL-enabled applications, such as financial trading, which could potentially surpass the previously used approaches. Indeed, there has ...

Multi-step forecasting is considered as an open challenge in time-series analysis. Although several approaches were proposed to address this complex prediction problem, none of them could secure the development of an efficient as well as a ...

As the main component of the new energy battery, the safety vent usually is welded on the battery plate, which can prevent unpredictable explosion accidents caused by the increasing internal pressure of the battery. The welding quality of safety ...$$$$$$

The growing usage of digital microphones has generated an increased interest in the topic of Acoustic Anomaly Detection (AAD). Indeed, there are several real-world AAD application domains, including working machines and in-vehicle intelligence (...

Presently, most markets are extremely saturated and, as a result, businesses are highly competitive. Hence, avoiding the loss of preexisting customers is pivotal, deeming the prediction of customer loss crucial to efficiently target potential ...

The identification of the source in groundwater pollution is the only way to drastically deal with resulting environmental problems. This can only be achieved by an appropriate monitoring network, the optimization of which is prerequisite for the ...

Tailored analytics play a key role in the successful delivery of cultural content to huge and diverse groups. Primarily the latter depends on a number of information retrieval factors determining user experience quality, most prominently precision,...

The growing need to use online services has made it necessary to ensure protection against all kinds of cyber-threats. This research effort aims to tackle network security problems as follows: It introduces the hybrid intrusion detection system ...

The accurate diagnosis of Alzheimer’s disease (AD) in the early stages, such as significant memory concern (SMC) and mild cognitive impairment (MCI), is essential in order to slow its progression through timely treatment. Recent achievements have ...

Big data has reignited research interest in machine learning. Massive quantities of data are being generated regularly as a consequence of the development in the Internet, social networks, and online sensors. Particularly deep neural networks ...

COVID-19 is an infectious disease with its first recorded cases identified in late 2019, while in March of 2020 it was declared as a pandemic. The outbreak of the disease has led to a sharp increase in posts and comments from social media users, ...

Liver segmentation is a basic and important procedure in liver transplantation surgery as well as in liver volumetric assessment. What is commonly done in clinical practice and research is the time-consuming manual delineation of liver regions. ...

In recent years, there has been an interest in visual sports analytics, and especially in player and ball detection, action recognition, and camera pose estimation in various sports. The greatest interest is associated with football or soccer. The ...

Optical fiber links are customarily monitored by Optical Time Domain Reflectometer (OTDR), an optoelectronic instrument that measures the scattered or reflected light along the fiber and returns a signal, namely the OTDR trace. OTDR traces are ...

Feature selection (FS) is an important area of research in medicine and genetics. Cancer classification based on the microarray gene expression data is a challenge in this area due to its high-dimensional features and small sample size. This can ...

Multi-objective evolutionary algorithms face many challenges in optimizing mixed-variable multi-objective problems, such as quantization error, low search efficiency of discontinuous discrete variables, and difficulty in coding non-integer ...

In this work, a comprehensive review of the multi-objective grey wolf optimizer (MOGWO) is provided. In multi-objective optimization (MO), more than one objective function must be considered at the same time. To deal with such problems, a priori ...

Selecting relevant feature subsets is vital in machine learning, and multiclass feature selection is harder to perform since most classifications are binary. The feature selection problem aims at reducing the feature set dimension while ...

To solve the problem that the existing semi-supervised FISHER discriminant analysis algorithm (FDA) cannot effectively use both labeled and unlabeled data for learning, we propose a semi-supervised Kernel local FDA Algorithm based on density peak ...

Stress is burgeoning in today’s fast-paced lifestyle, and its detection is imperative. An electroencephalography (EEG) technique is used to identify the brain’s activities from the brain’s electrical bio-signals. However, only a highly trained ...

Multi-scale object detection is one of the focuses of object detection, which is particularly vital for ship detection. In order to achieve the desired effects, most advanced Convolutional Neural Network-based detectors enumerate and make ...

Multiclass classification is a fundamental and challenging task in machine learning. The existing techniques of multiclass classification can be categorized as (1) decomposition into binary (2) extension from binary and (3) hierarchical ...

This paper deals with a new design of a hybrid fuzzy super-twisting sliding mode controller (HFSTSMC) for a three-phase induction motor (IM) controlled by the rotor flux orientation technique. Super-twisting sliding mode control is employed as a ...

This work proposes a new intelligent disease prediction system for predicting the disease and also knowing the current status of the dead diseases such as diabetic, heart and cancer diseases. More number of people are affecting and losing their ...

Surface soil moisture (M_SS) is a key factor governing environmental interactions in any catchment. Energy flux between soil and atmosphere, soil temperature, and heat diffusion in soil are examples of impressible interactions. Consequently, the ...

Broad learning system (BLS) is an emerging neural network with fast learning capability, which has achieved good performance in various applications. Conventional BLS does not effectively consider the problems of class imbalance. Moreover, ...

The object tracking field continues to evolve as an important application of computer vision. Real-time performance is typically required in most applications of object tracking. The recent introduction of Convolutional Neural network (CNN) ...