Neural Computing and Applications

With the growing interest in green logistics, the electric vehicles have been widely used as an important distribution means. In this paper, the electric vehicle routing problem with battery swap consideration and mixed time windows constraints (...

Multiple sclerosis (MS) is one of the most common inflammatory neurological diseases in young adults. There are three types of MS: (1) In relapsing remitting MS (RRMS), people have temporarily periods of relapses (attacks) for days or weeks, and ...

Artificial intelligence-based Medical Image Analysis (AI-MIA) has achieved significant advantages in accuracy and efficiency in various biomedical applications. However, most existing deep learning (DL) models have a fixed network structure and ...

Recently, few-shot learning has received considerable attention from researchers. Compared to deep learning, which requires abundant data for training, few-shot learning only requires a few labeled samples. Therefore, few-shot learning has been ...

This paper constructs an optimal scheduling model for combined heat and power generation units with heat storage and wind power generation considering carbon transaction costs and optimizes the output of each unit to reduce wind curtailment rate, ...

The viability of thermal waste-to-energy (WTE) plants and its optimal performance have informed intelligent predictive modelling of its significant variables critical to optimal energy recovery and plant operational planning using machine learning ...

Seagull optimization algorithm (SOA) is a recent bio-inspired technique utilized to improve the constrained large-scale problems in low computational cost and quick convergence speed. However, the globally optimized search space for the SOA is ...

Simplifying fuzzy models, including those for predicting time series, is an important issue in terms of their interpretation and implementation. This simplification can involve both the number of inference rules (i.e., structure) and the number of ...

Face-based video retrieval (FBVR) is the task of retrieving videos that containing the same face shown in the query image. In this article, we present the first end-to-end FBVR pipeline that is able to operate on large datasets of unconstrained, ...$$

Recently, high-performance multi-channel microstrip filters are widely demanded by modern multi-service communication systems. Designing these filters with both compact size and low loss is a challenge for the researchers. In this paper and for ...

This study is conducted to build a multi-criteria text mining model for COVID-19 testing reasons and symptoms. The model is integrated with a temporal predictive classification model for COVID-19 test results in rural underserved areas. A dataset ...

Surface temperature is one of the first ocean variables investigated. Ocean temperature is a key indicator of global climate change. The anomalies in ocean temperature have caused significant deterioration of marine systems. Existing works on ...

Compared with RGB salient object detection (SOD) methods, RGB-D SOD models show better performance in many challenging scenarios by leveraging spatial information embedded in depth maps. However, existing RGB-D SOD models prone to ignore the ...

Investigating vibration signals is an effective technique for assessing system malfunction. However, extraction of weak flaw characteristics of shaking signals with large noise is difficult. Therefore, a new approach using singular spectrum ...${}_{\mathrm{}}$

Session-based recommendation aims to recommend the next item of an anonymous user session. Previous models consider only the current session and learn both of the user’s global and local preferences. These models fail to consider an important ...

Missing data imputation aims to accurately impute the unobserved regions with complete data in the real world. Although many current methods have made remarkable advances, the local homogenous regions, especially in boundary, and the reason of the ...

One of the most important aspects of people's everyday diet is edible oils. Good quality cooking oil plays a key role in one's health. Due to the increased demand for oil in both the international and domestic markets, vendors often mix the high-...

The traveling salesman problem (TSP) is one of the most popular combinatorial optimization problems today. It is a problem that is easy to identify but hard to solve. Therefore, it belongs to the class of NP-hard optimization problems, and it is a ...

In this paper, conductive polymer-based composites in order to have higher electrical conductivity have been constructed using different nanoparticles and numerically considered by different classification techniques. Due to non-conducting feature ...

Multi-space evolutionary search ($\mathrm{MSES}$) is a recently proposed paradigm to optimize across multiple solution spaces for solving a large-scale optimization problem. $\mathrm{MSES}$ allocates the computational resource equally on each search space. However, ...$\mathrm{}$$\mathrm{}$$\mathrm{}\mathrm{}$

We propose a tourist attraction IoT-enabled deep learning-based recommendation system to enhance tourist experience in a smart city. Travelers will enter details about their travels (traveling alone or with a companion, type of companion such as ...

Swarm-based metaheuristic optimization algorithms have demonstrated outstanding performance on a wide range of optimization problems in both science and industry. Despite their merits, a major limitation of such techniques originates from non-...${}^{}$

High-quality clear image can not only bring a good subjective feeling, but also provide good performance guarantee for subsequent computer vision tasks in practical industrial applications. How to improve the low-light image quality and obtain ...

Feature extraction, feature clustering, feature selection are suitable to enhance learning performance, reduce computational complexity, create better generalizable models, and reduce required storage. Although there are several feature reduction ...

It has been of great interest in the neuroimaging community to model spatiotemporal brain function and related disorders based on resting state functional magnetic resonance imaging (rfMRI). Although a variety of deep learning models have been ...

The undrained shear strength of the sensitive clays is an important parameter for the design of the foundation of the civil engineering structures. In this study, novel hybrid machine learning approaches, namely ANFIS-CA and ANFIS-PSO, are ...

Curtain grouting efficiency evaluation is vital to ensure the safety and stability of dam foundation constructions. However, the existing grouting efficiency evaluations rarely consider the intrapersonal uncertainty and interpersonal uncertainty ...

With the growing of economic globalization and world economic integration, customer demands are becoming increasingly personalization and diversification. How to design a reasonable schedule scheme becomes the key point of industries. Flexible job ...

The automatic voltage regulator (AVR) system is commonly used in power systems to remain terminal voltage of generator at a specified level. The terminal voltage level is controlled by utilizing various controllers in an AVR system. Researchers ...

Coconut (Cocos nucifera) is one of the major plantation crops in Sri Lanka. It has paved the way for establishing many industries due to versatility of the crop earning significant income to the country. One of the most important export products ...