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Time Series Forecasting Using Online Performance-based Ensemble Deep Random Vector Functional Link Neural Network
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Time series forecasting remains a challenging task in data science while it is of great relevance to decision-making in various industries such as transportation, finance, electricity resource management, meteorology. ...
Representation learning using deep random vector functional link networks for clustering: Representation learning using deep RVFL for clustering
(
Elsevier Ltd
, 2022 , Article)
Random Vector Functional Link (RVFL) Networks have received a lot of attention due to the fast training speed as the non-iterative solution characteristic. Currently, the main research direction of RVFLs has supervised ...
Situation Awareness Recognition Using EEG and Eye-Tracking data: a pilot study
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Since situation awareness (SA) plays an important role in many fields, the measure of SA is one of the most concerning problems. Using physiological signals to evaluate SA is becoming a popular research topic because of ...
Deep Reservoir Computing Based Random Vector Functional Link for Non-sequential Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Reservoir Computing (RC) is well-suited for simpler sequential tasks which require inexpensive, rapid training, and the Echo State Network (ESN) plays a significant role in RC. In this article, we proposed variations of ...
Hybrid Multi-Objective Optimization Approach With Pareto Local Search for Collaborative Truck-Drone Routing Problems Considering Flexible Time Windows
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
The collaboration of drones and trucks for last-mile delivery has attracted much attention. In this paper, we address a collaborative routing problem of the truck-drone system, in which a truck collaborates with multiple ...
Sample-Based Data Augmentation Based on Electroencephalogram Intrinsic Characteristics
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Deep learning for electroencephalogram-based classification is confronted with data scarcity, due to the time-consuming and expensive data collection procedure. Data augmentation has been shown as an effective way to improve ...
A Voting-Mechanism-Based Ensemble Framework for Constraint Handling Techniques
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Effective constraint handling techniques (CHTs) are of great significance for evolutionary algorithms (EAs) dealing with constrained optimization problems (COPs). To date, many CHTs, such as penalty function, superiority ...
Automatic variable reduction
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
A variable reduction strategy (VRS) is an effective method to accelerate the optimization process of evolutionary algorithms (EAs) by simplifying the corresponding optimization problems. Unfortunately, the VRS is manually ...
An Enhanced Multi-Phase Stochastic Differential Evolution Framework for Numerical Optimization
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Real-life problems can be expressed as optimization problems. These problems pose a challenge for researchers to design efficient algorithms that are capable of finding optimal solutions with the least budget. Stochastic ...
DQN based Blockchain Data Storage in Resource-constrained IoT System
(
Institute of Electrical and Electronics Engineers Inc.
, 2023 , Conference Paper)
Applying blockchain technology in the Internet of Things (IoT) systems to realize massive data storage is a promising technology, which can eliminate the dependence of IoT on central servers and protect data security ...