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- research-articleFebruary 2024
Multiple passive-sensor distributed target tracking approach with Machine Learning Feedback
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122344AbstractIn this paper, a novel recursive state estimation approach in three-dimensional space for a non-maneuvering target is developed. The proposed technique employs angle and amplitude information in a distributed fusion setup, tackling the issue of ...
Highlights- Multi-Sensor Distributed tracking with local tracking and centralized track.
- The deep learning algorithm complements the Bayesian target tracking solution.
- Confidence level from CNN predictions is used to complement IPDA at local ...
- research-articleFebruary 2024
NOA-LSTM: An efficient LSTM cell architecture for time series forecasting
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122333AbstractThe application of Machine learning and deep learning techniques for time series forecasting has gained significant attention in recent years. Numerous endeavors have been devoted to automating forecasting through the utilization of cutting-edge ...
- research-articleFebruary 2024
Improving conformalized quantile regression through cluster-based feature relevance
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122322AbstractConformalized quantile regression, a cutting-edge and model-agnostic algorithm, has emerged as a recent innovation to generate valid prediction intervals on finite samples while addressing heteroscedasticity. It starts by employing quantile ...
Highlights- A novel algorithm for tabular data that generates valid prediction intervals while handling heteroscedasticity.
- Computationally cheap, no retraining is involved nor necessary, under the mild assumption of exchangeability.
- ...
- research-articleFebruary 2024
SARAH-M: A fast stochastic recursive gradient descent algorithm via momentum
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122295AbstractAs a simple but effective way, the momentum method has been widely adopted in stochastic optimization algorithms for large-scale machine learning problems and the success of stochastic optimization with the momentum term for many applications in ...
Highlights- The efficacy of the variance reduced method with momentum is verified.
- An adaptive variance reduced method with momentum is proposed.
- The convergence properties of the proposed methods are provided.
- Experimental results show ...
- research-articleFebruary 2024
Decomposition strategy and attention-based long short-term memory network for multi-step ultra-short-term agricultural power load forecasting▪
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122226AbstractAccurate forecasting of the agricultural power load is important for rural electricity networks’ safe and stable operation. But it is more uncertain and difficult to forecast than industrial, commercial, and residential loads. Multivariate time ...
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- research-articleFebruary 2024
Spatio-temporal modeling of climate change impacts on drought forecast using Generative Adversarial Network: A case study in Africa
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122211AbstractDrought is an extreme weather event, affecting the ecological conditions of vegetation and agricultural productivity, poses challenges for millions of people in Africa, and its long-term prediction is definitely important. Accurate drought ...
Highlights- Proposes an advanced GAN forecasting model based on CNN-LSTM for agricultural drought.
- Investigates the impacts of climate change on spatial and temporal drought variation.
- Identifies multivariate remote sensing data over Africa ...
- research-articleFebruary 2024
Adapt to small-scale and long-term time series forecasting with enhanced multidimensional correlation
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PDhttps://doi.org/10.1016/j.eswa.2023.122203AbstractMultivariate time series forecasting aims to predict time series data comprising several linked variables or characteristics and is frequently used in stock forecasting, energy forecasting, etc. The tough task is to acquire further historical ...
- research-articleFebruary 2024
Mining a lottery for a favorable jackpot▪
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PDhttps://doi.org/10.1016/j.eswa.2023.122063AbstractA lottery offers rare opportunities for a favorable wager with a positive expected ticket value. We test various data mining methods for predicting when such opportunities may arise under suitable jackpot conditions. Two models – a linear and ...
Highlights- Mega Millions and Powerball lotteries sometimes offer a fair jackpot wager.
- Predict a fair wager based on jackpot size and number of prizes in last drawing.
- Logistic regression and classification decision tree predict a favorable ...
- research-articleFebruary 2024
A novel clustering method for complex signals and feature extraction based on advanced information-based dissimilarity measure
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PDhttps://doi.org/10.1016/j.eswa.2023.122011Highlights- Generalization of binary sequences to multivariate improves data representation.
- The weighted-probability of pattern occurrence is constructed based on complexity.
- The MDS based on the novel dissimilarity measure is constructed.
In this paper, a new dissimilarity measure for more accurate feature extraction and clustering is put forward. The method is proposed from the perspective of the weighted-probability distribution of dispersion patterns and their rank order ...
- research-articleFebruary 2024
Semi-supervised contrastive regression for pharmaceutical processes
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PDhttps://doi.org/10.1016/j.eswa.2023.121974AbstractArtificial intelligence methods of time series are starting to play an increasing role in the pharmaceutical field, and in recent years, there have been significant advances in self-supervised representation learning for time series data. However,...
Highlights- Adaptive segmented augmentation method.
- Supervised contrastive loss for regression task.
- Novel semi-supervised contrastive learning framework.
- Representation learning for pharmaceutical time series.
- research-articleFebruary 2024
Quasi-synchronization of stochastic heterogeneous networks via intermittent pinning sampled-data control
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121867AbstractThis paper is mainly concerned with the quasi-synchronization of stochastic heterogeneous networks (SHNs). Furthermore, the control strategy adopted here combines the advantages of aperiodically intermittent pinning control (AIPC) and sampled-...
Highlights- Some less conservative criteria for quasi-synchronization are derived.
- A novel control method, named aperiodically intermittent pinning sampled-data control, is designed.
- The control/rest interval distribution is described by the ...
- research-articleFebruary 2024
Local causal structure learning with missing data▪
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121831AbstractLocal causal structure learning aims to discover and distinguish the direct causes and direct effects of a target variable. However, the state-of-the-art algorithms for local causal structure learning fail to perform well when dealing with ...
- research-articleFebruary 2024
Symmetric Renyi-Permutation divergence and conflict management for random permutation set
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121784AbstractRecently, a theory called random permutation set (RPS) is proposed, which is the extension of Dempster–Shafer evidence theory. It defines a permutation event space (PES) to represent the order of events and uses the RPS to represent the support ...
- research-articleFebruary 2024
Real measurement data-driven correlated hysteresis monitoring model for concrete arch dam displacement
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121752AbstractDisplacement is an important indicator reflecting the safety performance of concrete arch dams and displacement monitoring models are widely adopted to analyze the health and serviceability of concrete arch dams. The measured data shows that the ...
- research-articleFebruary 2024
A stock series prediction model based on variational mode decomposition and dual-channel attention network
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121708AbstractDue to the comprehensive impact of external factors (politics, economy, market, etc.) and internal factors (organizational structure, management ability, innovation capability, etc.), stock series exhibit strong volatility. Coupled with their ...
Highlights- Series is decomposed into some approximately stationary series by the VMD method.
- We combined LSTM and TCN to form a dual-channel network.
- The self-attention mechanism is introduced into the dual-channel network.
- The proposed ...
- research-articleFebruary 2024
A novel multivariate time-lag discrete grey model based on action time and intensities for predicting the productions in food industry
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121627AbstractThe food industry is a pillar industry and plays an important role in the development of China's national economy. In view of the complex environments and the characteristics of fluctuating development in which the Chinese food industry are ...
- review-articleFebruary 2024
Higher-order moments in portfolio selection problems: A comprehensive literature review
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121625AbstractMarkowitz’s portfolio selection model has been the biggest step-forward in financial decision making and has been the central point of research since its inception. The mean–variance model led to the foundation of the modern portfolio theory and ...
- research-articleFebruary 2024
Modelling and forecasting high-frequency data with jumps based on a hybrid nonparametric regression and LSTM model
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121527AbstractHigh-frequency financial data is more difficult to predict than low-frequency data because it possesses nonlinearity, nonstationarity, higher volatility, and long memory and is frequently accompanied by the jump phenomena. In this paper, the ...
- research-articleFebruary 2024
Data-driven interpretable ensemble learning methods for the prediction of wind turbine power incorporating SHAP analysis
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121464AbstractWind energy increasingly attracts investment from many countries as a clean and renewable energy source. Since wind energy investment cost is high, the efficiency of a potential wind power plant should be determined using wind power prediction ...
- research-articleFebruary 2024
From machine learning to semi-empirical formulas for estimating compressive strength of Ultra-High Performance Concrete
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121456AbstractAlthough some machine learning (ML) models have successfully developed for ultra-high-performance concrete (UHPC), they do not provide insights and explicit relations between all input variables and its compressive strength. This paper will ...
Highlights- Explicit formulas are derived to predict the compressive strength of UHPC.
- Multivariate polynomial regression and automated feature engineering are used.
- Relative feature importance and partial dependence plots are used to explain ...