Applied Soft Computing

Industrial cut tobacco drying is one of the most important processes in cigarette production, which affects the taste, cut tobacco consumption and other indicators of cigarette products. Due to the complicated process and parameters ...

• A complete first principle model for industrial cut tobacco drying process is established.

The learning of high-quality stock representations is one of the keys to predicting stock movements effectively. Current studies have been negatively impacted by stochasticity in stock prices, resulting in inadequate representation ...

• The contrastive learning method is introduced into stock data analysis.
• A ...

Frequency instability has been a growing problem in recent years due to the rising penetration of distributed generating systems in the format of Microgrids (MGs), which are powered by renewable energy sources (RESs) with an ...

• The real-time viability of the proposed approach is evaluated using OPAL-RT based real-time assessments.

As a metabolic disease, diabetes is a serious threat to human health, in which type 2 diabetes (T2D) constitutes about 90% of diabetic cases. As the disease progresses, T2D often comes with various complications such as kidney disease ...

• This paper develops a risk prediction model for type 2 diabetes complication forecast.

The multi-objective optimization algorithms (MOO) are used to obtain the best compromising solutions when two or more objective functions need to be optimized simultaneously. The convergence and diversity are critical factors to ...

• Combined economic emission dispatch problem is solved by ABC-NSGA-II Algorithm.

Early intervention and prevention of chronic diseases is a fundamental way to reduce disease incidence. Due to the complex pathogenic factors of disease, the assessment of disease risk requires consideration of the influence of ...

• The notion of multiple hybrid attribute information systems (MHAISs) is presented.

This study presents the game modeling of the multi-objective frequency assignment problem (FAP) in cellular networks considering two conflicting objectives: interference and separation costs, while respecting separation constraints, ...

• A model based on game theory is proposed to solve a multi-objective optimization problem.

In response to the low-carbon development strategy, the new energy vehicle has become one crucial and recognized tool to satisfy the emission reduction requirements, the representative advance of the new energy vehicle is its ...

• This paper improves intelligent drive technique by introducing driver’s subjective guidance.

The need for effective electronic waste (e-waste) management practices has received wide attention due to increased societal awareness; however, the existence of challenges adds difficulties. This study identifies these critical e-...

• This study analyzes the e-waste mitigation strategies by taking into account the challenges involved.

In geotechnical engineering, surrogate modeling is a vital technique for enhancing computational efficiency when faced with limited and costly samples. However, most adaptive sequential sampling (ASS) methods use the Kriging model, ...

• We proposed an effective adaptive sequential sampling method that combines ANN_MCD and RF.

One particular kind of evolutionary algorithms known as Estimation of Distribution Algorithms (EDAs) has gained the attention of the aerospace industry for its ability to solve nonlinear and complicated problems, particularly in the ...

• An adaptive approach is developed for low-thrust space trajectory optimization.

Sequential recommendation has recently played an important role on various platforms due to its ability to understand users’ intentions from their historical interactions. However, modeling user’s intention on time-based ...

• A novel Contrastive Learning with Frequency Domain for Sequential Recommendation.

Healthcare services create medical waste that may be dangerous to healthcare personnel, patients, the general public, and the environment. Medical waste disposal method selection is among the most important decisions that must be made ...

• CRITIC-WASPAS method is extended with single and interval-valued spherical fuzzy sets.

The Offline Nanosatellite Task Scheduling (ONTS) problem poses a complex optimization challenge, focused on maximizing the number of tasks executed by a satellite in orbit while adhering to Quality of Service constraints such as ...

• Column-generation-based genetic algorithm inspired on branch-and-price.
• First ...

Over the past few years, stacked generalization has emerged as a promising approach for predicting the concentration of PM2.5, but its use is often associated with reduced efficiency due to computational demands. In this study, we ...

• RBOSR reduces computational resources and training time for improved PM2.5 stacked model efficiency.

Ultra supercritical power plant (USC) is a complex system associated with nonlinearity, uncertainties and multivariable couplings. Generally, it is difficult to build an accurate model to approximate the dynamic behavior of USC. This ...

• By partitioning, the nonlinearity of the target is diluted to an acceptable range.

This research work discusses a noise-robust picture fuzzy clustering method with an application to the MRI image segmentation problem. The MRI images suffer from the problem of noise and non-linear structures. Although there are many ...

• Modified total Bregman divergence driven picture fuzzy clustering with local information is proposed for human brain MRI image segmentation task in the ...

This paper investigates the problem of cooperative guidance of two pursuers against an evader equipped with higher maneuverability. The goal is that the distance between the Evader and at least one of the pursuers becomes less than a ...

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• A new heuristic cooperative guidance algorithm is proposed for nonlinear kinematics of the pursuers and the target engagement.

Accurate and robust collection of plant phenotypic data offers theoretical as well as technical support to support the growth of crop science and to ensure ecological security, agricultural growth, and food security. Identifying ...

• GAN and U-Net based Taylor Coot: An optimal framework for plant region segmentation is developed through fusion mechanism.

Previously, doctors interpreted diseases and their outcomes according to their experience in diagnosis. However, with the rapid increase in technology and population, the task of examining the patient becomes cumbersome and sometimes ...

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• To explore quantum computing in healthcare sector.
• To devise an umbrella based ...

Decision-making under evacuation environment is extremely complex due to the variety of aspects to be considered as well as the necessity of high-speed reaction. Therefore, the elaboration of the evacuation pattern, particularly, ...

• The hesitant fuzzy TOPSIS approach to calculate the priority order of shelters with unknown attribute weights.

Accurate prediction of floating offshore platform motion (FOPM) is very important to control the movement of the platform and the normal operation of the equipment on the platform. However, the accurate prediction of FOPM is very ...

• This paper proposes a hybrid forecasting approach of FOPM to obtain accurate forecasting performances.

Compiling quantum circuits on target quantum hardware architectures is one of the key issues in the development of quantum algorithms, and the related problem is known as the Quantum Circuit Compilation Problem (QCCP). This paper ...

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• A genetic algorithm to tackle the Quantum Circuit Compilation Problem is described.

In recent years, several population-based evolutionary and swarm algorithms have been developed and used in the literature. This work introduces an improved Cultural Algorithm with a modified selection function and a dynamic α-...

• mCA-αC is an enhanced version of CAs with a modified selection function.

The development of computational intelligence based approaches for the compression of graphs is an under-explored area of research. Further, compression of weighted graphs is significantly more complicated than compression of ...

• A multi-objective approach is applied to the problem of weighted graph compression.

The determination of characteristic points of bioimpedance curves is crucial to the analysis of bioimpedance signals. Traditional methods need to calculate the derivative of the bioimpedance curve and rely on the help of other ...

• The aim is to automatically determine the positions of characteristic points of bioimpedance signals.

Various deep learning architectures have been developed to capture long-term dependencies in time series data, but challenges such as overfitting and computational time still exist. The recently proposed optimization strategy called ...

• An efficient optimizer for improving generalization in time series data is proposed.

Automated and intelligent design in the construction industry has drawn considerable attention in these years along with the modern industrial revolutions. However, the achievement is strongly held up by the high unreliability in the ...

• A generative design system for tunnel excavation assisted by SHAP is developed.

As the modern energy systems is becoming more complex and flexible, accurate load forecasting has been the key to scheduling power to meet customers’ needs, load switching, and infrastructure development. In this paper, we propose a ...

• Propose a novel short-term load forecasting framework that integrates ResNet and LSTM.