Applied Soft Computing

Proper management and treatment of food waste have become a key concern due to its significant environmental, social, and economic ramifications. The selection of the most appropriate food waste treatment method among a set of ...

• Uncertainty in food waste treatment selection is handled using neutrosophic concept.

Face inpainting, a special case of image inpainting, aims to complete the occluded facial regions with unconstrained pose and orientation. However, existing methods generate unsatisfying results with easily detectable flaws. There are ...

• FIFPNet predicts and fuses face semantic information to complete face inpainting.

The occurrence of natural and man-made disasters usually leads to significant social and economic disruption, as well as high numbers of casualties. Such occurrences are difficult to predict due to the huge number of parameters with ...

• A novel route planning scheme for rescue vehicles in disasters is proposed.
• ...

In recent years, many works spring out to adopt the forecast-based approach to support the investment decision in the financial market. Nevertheless, most of them do not consider mining the hidden patterns in the cross-regional ...

• Present a method for learning the hidden patterns of the financial time-series.

Recently the literature of Simulation Optimization for solving stochastic constrained optimization problems has been substantially increasing. From the optimization perspective, the population based meta-heuristics algorithms, such as ...

• Proposed two-stage simulation assisted EA for chance constraints.
• Minimum risk ...

This paper presents an effective multi-objective Jaya (EMOJaya) algorithm to solve a multi-objective job-shop scheduling problem, aiming to simultaneously minimise the makespan, total flow time and mean tardiness. A strategy based on ...

• A multi-objective job-shop scheduling problem is studied.
• An effective multi-...

The new type of coronavirus, COVID 19, appeared in China at the end of 2019. It has become a pandemic that is spreading all over the world in a very short time. The detection of this disease, which has serious health and socio-economic ...

• Using pre-trained CNN models is an effective way to extract deep features
• ...

To maintain the stability and punctuality of bus systems, an accurate forecast of arrival time is essential to devise control strategies to prevent bus bunching especially under congested traffic conditions. Transit agencies provide ...

• FDA and BSVR to anticipate short-term travel time uncertainties.
• Probabilistic ...

We discuss a planning model with load-dependent lead times for making order acceptance decisions in multi-product, multi-stage manufacturing systems. Semiconductor wafer fabrication facilities (wafer fabs) belong to this class of ...

• Integrated planning and order acceptance problems are studied.
• Workload-...

A key aspect for the forklifts is the state-of-health (SoH) assessment to ensure the safety and the reliability of uninterrupted power source. Forecasting the battery SoH well is imperative to enable preventive maintenance and hence to ...

• A novel gradient-boosting model for state-of-health of lithium-ion battery packs

How to design a reasonable classification method to identify the states is a critical step in rolling bearing fault diagnosis. Along with labeled samples, the Laplacian regularization (LapR) classification method, a graph-based semi-...

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• A novel fault diagnosis method of rolling bearing based on LapR is proposed.
• ...

The evolution of digital communications has resulted in new services that require from secure and robust connections. Nowadays, a signal must be transmitted to distant nodes, and the quality of the signal deteriorates as the distance ...

• We propose an Iterated Greedy approach for the Regenerator Location Problem (RLP).

Ransomware is a form of malicious software which when deployed encrypts or locks the files and demands a ransom to have the files decrypted and accessible. In today’s digital world, devices connected to the network are vulnerable to ...

• An ACOLBSR algorithm is proposed to filter ransomwares.
• The ant agent finds the ...

Vehicle stability and energy efficiency are important considerations in vehicle engineering. In this context, the current paper presents an energy saving strategy for hybrid electric vehicles that incorporates vehicle lateral dynamic ...

• We model the nonlinear vehicle lateral dynamics of a bus with the so-called Takagi-Sugeno fuzzy approach and combine with an H_{\infty } state-feedback ...

Banks face the task of improving the accuracy in predicting the behavior of individuals who utilize credit cards, as issuing cards to an appropriate applicant is considered an important matter. Credit card debt that is overdue by at ...

• The applications of predictive intelligence enhance the prediction of credit defaults.

The main challenges in large scale group decision making (LSGDM) problem are how to tackle with the great number of participants and how to achieve a common solution accepted by most of participants. To address these challenges, in ...

In 2020, a novel coronavirus disease became a global problem. The disease was called COVID-19, as the first patient was diagnosed in December 2019. The disease spread around the world quickly due to its powerful viral ability. To date, ...

• A dendritic neural regression is applied to predict the COVID-19 transmission trend.

Energy Efficiency is a key concern for future fog-enabled Internet of Things (IoT). Since Fog Nodes (FNs) are energy-constrained devices, task offloading techniques must consider the energy consumption of the FNs to maximize the ...

• The paper presents two energy prediction techniques for fog computing networks.

The performance of differential evolution (DE) algorithm significantly depends on mutation strategy. However, there are six commonly used mutation strategies in DE. It is difficult to select a reasonable mutation strategy in solving ...

• A mixed mutation strategy DE algorithm based on deep Q-network (DQN), called DEDQN is proposed.

The driving strategy of the driver is one of the critical factors which affect the energy consumption of the vehicle. However, it is often overlooked in the researches of energy management. Moreover, there are few studies devoted to ...

• A multi-objective optimized driving strategy for dual-motor EVs is proposed.
• ...

The vision behind this paper looks ahead to evolutionary robot systems where morphologies and controllers are evolved together and ‘newborn’ robots undergo a learning process to optimize their inherited brain for the inherited body. ...

• We achieve the task of directed locomotion in evolvable modular robots rather than a typical undirected gait learning.

Information fusion has traditionally been a concern. In the fusion process, how to effectively take care of the ambiguity and uncertainty of data is a fascinating problem. Dempster–Shafer evidence theory shows powerful functions in ...

• Proposed a new information fusion method based on Dempster–Shafer Evidence Theory (DST) and K-means clustering.

The Vehicle Routing Problem (VRP) is a classical NP-hard combinatorial optimization problem. In recent years, a lot of heuristic algorithms have been proposed for optimizing the problem, and many simulation and practical experiments ...

This study proposes a two-echelon location routing framework for cash-in-transit. In order to mitigate the risk of robbery in cash transportation, a dynamic risk index is considered. The utilized risk function encompasses both the ...

• A bi-objective two-echelon LRP with a dynamic risk index is proposed.
• Several ...

A novel coronavirus (COVID-19) has globally attracted attention as a severe respiratory condition. The epidemic has been first tracked in Wuhan, China, and has progressively been expanded in the entire world. The growing expansion of ...

• Introducing a deep ensemble RL-based method to diagnose COVID-19 from X-ray images.

Nowadays, many extended rough set models are proposed to acquire valuable knowledge from interval-valued information system. These existing models mainly focus on different forms of similarity relations. However, most of these ...

• We present a novel fuzzy neighborhood rough set for interval-valued information systems with fuzzy decision.

Multi-criteria decision making (MCDM) is a common method used to solve complex decision-making problems. One such method, TODIM (TOmada de Decisão Iterativa Multicritério), is derived from prospect theory, which considers the ...

• Present the literature review of the extensions of fuzzy TODIM.
• Give extensions ...

Neural architecture design is one of the critical tasks for deep neural models because of the high variety of structure options. This research proposes an adaptive neural architecture optimization (ANAO) model to optimize the ...

• Propose a predictive deep model structure optimization process.
• Improve the ...

Channel equalization is a basic requirement of wireless receiver to alleviate the effects of inter symbol interference (ISI) that helps in faithful reconstruction of original information. The accuracy of channel state information (CSI) ...

• Sparse Adaptive Equalization Model for Indoor Communication System using Fuzzy rule based learning Parameter.