Expert Systems with Applications: An International Journal

• ACBFO and ISEDBFO are proposed based on original bacterial foraging optimization.

Bacterial foraging optimization (BFO) algorithm is a new swarming intelligent method, which has a satisfactory performance in solving the continuous optimization problem based on the chemotaxis, swarming, reproduction and elimination-...

• The venue recommendation is formulated as a ranking problem.
• A context-based ...

Venue recommendation has attracted a lot of research attention with the rapid development of Location-Based Social Networks. The effectiveness of venue recommendation largely depends on how well it captures users’ contexts or ...

• We propose a new neighbors finding method for CF based on subspace clustering.
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Recommender Systems (RS) are used to help people reduce the amount of time they spend to find the items they are looking for. One of the most successful techniques used in RS is called Collaborative Filtering (CF). It looks into the ...

• Tremor and voluntary movement of the upper limb are separated from IMUs signals.

Much attention has been given to the use of inertial sensors for remote monitoring of individuals suffering from neurological pathologies. However, the focus has been mostly on the detection of symptoms like ...

• Two variant fuzzy classifiers of a well-known fuzzy classifier were proposed.
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Interpretability of classification systems, which refers to the ability of these systems to express their behavior in an understandable way, has recently gained more attention and it is considered as an important requirement especially ...

• A novel hybrid algorithm (MHDA) based on Dragon Fly and PSO is proposed.
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Dragonfly algorithm (DA) is a recently proposed optimization algorithm based on the static and dynamic swarming behaviour of dragonflies. Due to its simplicity and efficiency, DA has received interest of researchers from different ...

• We present an approach to identify the winning team based on the polynomial classifier.

Football is the team sport that mostly attracts great mass audience. Because of the detailed information about all football matches of championships over almost a century, matches build a huge and valuable database to test prediction ...

• Novel distant supervision-based approach to Twitter account classification.
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Individuals use Twitter for personal communication, whereas businesses, politicians and celebrities use Twitter for branding purposes. Distinguishing Personal from Branding Twitter accounts is important for Twitter analytics. Existing ...

• We propose estimating the quality of a contrast pattern using unseen objects.
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Contrast patterns, which lie in the core of most understandable classifiers, are frequently evaluated by quality measures. Since many different quality measures are available, they should be compared to select the most appropriate for ...

• Traditionally, the probably approximately correct (PAC) learning refers the single concept class. We discuss the PAC framework of the multiple tasks in the ...

Joint inference is a fundamental issue in the field of artificial intelligence. The greatest advantage of the joint inference is demonstrated by its capability of avoiding errors from cascading and accumulating on a pipeline of ...

• A new spline based generalized non-linear filter.
• Adaptive spline function is ...

A new nonlinear filter, which employs an adaptive spline function as the basis function is designed in this paper. The input signal to this filter is used to generate suitable parameters to update the control points in a spline ...

• Multi-dimensional sensitivity analysis is crucial in multi-criteria decision making.

Multi-Criteria Decision Analysis (MCDA) enables decision makers (DM) and decision analysts (DA) to analyse and understand decision situations in a structured and formalised way. With the increasing complexity of decision support ...

• Extracting and using of time-dependent indices improved prediction accuracy.
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Since fresh water is limited while agricultural and human water demands are continuously increasing, optimal prediction and management of streamflows as a source of fresh water is crucially important. This study investigates and ...

• The random forests-based extreme learning machine ensemble model is proposed.
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Accurate and timely predicting values of performance parameters are currently strongly needed for important complex equipment in engineering. In time series prediction, two problems are urgent to be solved. One problem is how to ...

• An extensive comparison of Hebbian and Random input weights in SLFN networks.
• A ...

In this paper, we provide an experimental study for two unsupervised processes, namely, the random initialization and the Hebbian learning, which can be used to determine the input weights in Single-hidden Layer Feedforward Neural ...

• Deep learning networks are applied to stock market analysis and prediction.
• A ...

We offer a systematic analysis of the use of deep learning networks for stock market analysis and prediction. Its ability to extract features from a large set of raw data without relying on prior knowledge of predictors makes deep ...

• This paper proposes a new method for multicriteria group decision-making processes.

The problem-solving decision-making process often requires involvement of a group of individuals who have differing interests and conflicting multiple evaluation criteria. Therefore, the greatest concern in multiobjective group ...

• Fixing input sites in ensembles restrict learning movable and distant patterns.

In this paper, we introduce a new ensemble method specialized to sequential labeling for syntax analysis and propose a neural network framework adopting the ensemble for dependency parsing of natural sentences. The ensemble method ...

• We develop a novel prognostic method for estimating the RUL and its uncertainty.

We develop a novel prognostic method for estimating the Remaining Useful Life (RUL) of industrial equipment and its uncertainty. The novelty of the work is the combined use of a fuzzy similarity method for the RUL prediction and of ...

• Two metaheuristic algorithms (WOA and MFO) are used.
• These algorithms are ...

Determining the optimal thresholding for image segmentation has got more attention in recent years since it has many applications. There are several methods used to find the optimal thresholding values such as Otsu and Kapur based ...

• A novel evolutionary Fuzzy Rule-based System for modeling problems is proposed.

In this paper, we propose a novel Evolutionary Mamdani Fuzzy Rule-based System named DECO₃RUM (Differential Evolution based Cooperative and Competing learning of Compact Rule-based Models). The main advantage of DECO₃RUM is that it ...

It is well established that multiple EEG channels are required for various brain functionality studies, including classification tasks. Yet, due to the curse of dimensionality problem, the analysis of multiple channels may not lead to ...

• Multiple practical objectives of the integer programming model are provided.
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This paper considers a multi-objective aircraft recovery problem for airline disruption. An integer programming formulation is first established based on connection network with three conflicting objectives, where the first objective ...

• Neural network based hybrid recommender system utilizing review metadata is proposed.

In the context of recommendation systems, metadata information from reviews written for businesses has rarely been considered in traditional systems developed using content-based and collaborative filtering approaches. Collaborative ...

• A new classifier is presented to detect undesired short text comments.
• The ...

The popularity and reach of short text messages commonly used in electronic communication have led spammers to use them to propagate undesired content. This is often composed by misleading information, advertisements, viruses, and ...

• A model for predicting churn one day after registration in games is proposed.
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Customer churn is a widely known term in many industries, including banking, telecommunications and gaming. By definition, churn represents the act of a customer leaving a product for good. Most commonly, late customer churn is ...

• An international portfolio employs a currency overlay to manage currency exposure.

International financial portfolios can be exposed to substantial risk from variations of the exchange rates between the countries in which they hold investments. Nonetheless, foreign exchange can both generate extra return as well as ...

• Proposal to improve the expressive richness of any decision-making model results.

In general, traditional decision-making models are based on methods that perform calculations on quantitative measures. These methods are usually applied to assess possible solutions to a problem, resulting in a ranking of ...

• A model for temporal cluster analysis that reflects behavior patterns over time.

Cluster analysis often addresses a specific point in time, ignoring previous cluster analysis products. The present study proposes a model entitled Cluster Evolution Analysis (CEA) that addresses three phenomena likely to occur over ...