Applied Soft Computing

The problem of allocating students to supervisors for the development of a personal project or a dissertation is a crucial activity in the higher education environment, as it enables students to get feedback on their work from an ...

• We propose a multiobjective genetic approach for the student–supervisor allocation.

To overcome the limitation of single search strategy of grey wolf optimizer (GWO) in solving various function optimization problems, we propose a multi-strategy ensemble GWO (MEGWO) in this paper. The proposed MEGWO incorporates three ...

• A multi-strategy ensemble GWO is proposed to boost the precision and efficiency of the original GWO.

Although an economic time-series has an apparently random fluctuation over time, there exists certain regularity in the functional behavior of the series. This paper attempts to identify the regularly occurring structures in an ...

• This paper employs a novel approach for time-series segmentation, clustering of similar segments and labeling of the series with the known structured ...

A novel variant of particle swarm optimization with damping factor and cooperation mechanism (PSO-DFCM) to search the global optima in a large scale and high-dimensional searching space. In this optimal searching strategy, one balances ...

• A new parameter, damping factor, is introduced to adjust the position information inherited from the previous state.

Facial expressions are one of the most important characteristics of human behaviour. They are very useful in applications on human computer interaction. To classify facial emotions, different feature extraction methods are used with ...

• Facial expression recognition is performed using prior information about data.
• ...

Chaotic maps have been shown to be suitable for applications that require unpredictable behavior. In this paper, the chaotic maps are used for motion planning and control of a quadrotor for boundary surveillance purposes. The chaotic ...

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• Unpredictable 3D paths for a quadrotor is generated.
• This method is developed ...

In complex group decision-making, decision makers and decision attributes are the core of the relevant activities. Targeting the problem of scheme ranking and behavioural characteristics that exist in group decision-making, from the ...

• Construct a two-step optimization model to solve for the group consensus ideal scheme and its measure value matrix.

The Internet emerged as a powerful infrastructure for the worldwide communication and interaction of people. Some unethical uses of this technology (for instance spam or viruses) generated challenges in the development of mechanisms to ...

• Use semantic meaning of e-mail words to provide successful inputs for ML classifiers.

We present both sequential and data parallel approaches to build hierarchical minimum spanning forest (MSF) or tree (MST) in Euclidean space (EMSF/EMST) for applications whose input N points are uniformly or boundedly distributed in ...

• A newly proposed improvement of Bentley’s spiral search method specially adapted to EMST problems and its parallelism on GPU.

Manufacturing service supply chain (MSSC) optimization has been intensively studied to find an optimal service composition solution with the best quality of service (QoS) value. However, traditional MSSC optimization methods usually ...

• A networked correlation-aware manufacturing service composition model is proposed.

Given the international efforts in tackling climate change as well as the potential dependence on conventional energy imports and the adverse economic environment, countries in the European Union face significant challenges in the ...

• Supporting decisions in energy efficiency policy design is a challenging task.
• ...

Segmentation of brain magnetic resonance (MR) images has a significant impact on the computer-aided diagnosis and analysis. However, due to the presence of noise in medical images, many segmentation methods suffer from limited ...

• A fast DCT-based MR image segmentation approach proposed.
• The approach provides ...

Word-level machine translation (MT) quality estimation (QE) is usually formulated as the task of automatically identifying which words need to be edited (either deleted or replaced) in a translation T produced by an MT system. The ...

• Novel appproach predicting insertions in machine translation quality estimation.

Finding the best flow patterns (i.e., choices of resources) for a family of products is a key part of supply chain management. It primarily focuses on reasonable selecting suppliers for every component, selecting plants for assembling ...

• The complexity of a three-echelon SCM network is reduced greatly.
• The ...

Diabetes mellitus is one of the most common chronic diseases in the world. A remarkable point about chronic diseases is that patients may be involved in related complications throughout their lifetime. Management and control of chronic ...

• We propose a new hybrid fuzzy based algorithm to analyze the severity of damages caused by diabetes related complications.

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To ...

• MEKL-MP assigns high cost to minority samples to deal with imbalanced problems.

This paper describes the use of Kernel Ridge Regression (KRR) and Kernel Ridge Regression Confidence Machine (KRRCM) for black box identification of a surface marine vehicle. Data for training and test have been obtained from several ...

• Black box identification based on Conformal Predictors is used for marine vehicles.

A robust fusion algorithm based on Radial Basis Function (RBF) neural network with Takagi–Sugeno (TS) fuzzy model is proposed in view of the data loss, data distortion or signal saturation which is usually occurred in the process of ...

• A new weighted activation degree (WAD) is defined to calculate the firing strength of the fuzzy nodes.

This paper addresses the issue of computational resource allocation within the context of cooperative coevolution. Cooperative coevolution typically works by breaking a problem down into smaller subproblems (or components) and ...

• Where subproblems do not contribute equally to the overall objective value, allocating the budget uniformly to all subproblems is a waste of valuable ...

Most of the existing models for project portfolio selection are proposed on the framework of fixed investment horizon. One recent and promising strategy for project portfolio selection is flexible time horizon investment that can ...

• We propose two flexible time project portfolio models with reinvestment strategy.

Traditional multi-objective evolutionary algorithms have encountered difficulties when handling many-objective problems. This is due to the loss of selection pressure incurred by the growing size of objective space. A variety of ...

• Devise a multi-population framework to combine advantages of multiple operators.

Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unmanned Aerial Vehicles (UAVs), such as the quadrotor, have been based on batch learning techniques, therefore static in structure, and ...

• This paper presents at the first time the real-world application of a newly developed algorithm, namely McSIT2RFNN for online identification of rotary wing ...

The major difficulty in multi-objective optimization evolutionary algorithms (MOEAs) is how to find an appropriate solution which is able to converge towards the true Pareto Front with high diversity. In order to strengthen the ...

• We propose a new approach (EDV) that combines indicator I ε + with direction vectors to handle MaOPs.

In our state-of-the-art study, we improve neural network-based models for predicting energy consumption in buildings by parallelizing the CHC adaptive search algorithm. We compared the sequential implementation of the evolutionary ...

• A parallel approach is proposed based on recurrent neural networks.
• The method ...

Choosing an appropriate local optimal region in order to satisfy the location priorities and to guarantee enough robustness against measurement biases is desired in many optimization problems. To fulfill such aim, all locally convex ...

• A clustering method is introduced to approximate local convex regions of a Function.

In this work, the Synthetic Minority Over-sampling Technique (SMOTE) approach is adapted for high-dimensional binary settings. A novel distance metric is proposed for the computation of the neighborhood for each minority sample, which ...

• Novel SMOTE oversampling approach for imbalanced data sets.
• A novel distance ...

Price sensitivity is an outstanding business issue in companies and organizations that aim to undertake optimal managerial decisions for increasing sales and / or revenue. Hence, price sensitivity assessment has become an in fashion ...

• A machine learning approach is proposed to assess price sensitivity (PS).
• The ...

Hesitant fuzzy linguistic preference relations (HFLPRs) as an efficient and common tool to deal with decision-making problems have been widely used in real life. The consistency and consensus are the most two important topics for ...

• We establish a more time-saving consistency reaching and a consensus achieving model.

Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, ...

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• FMRS algorithm for minimizing response time on handling complex query.
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