Future smart cities: Requirements, emerging technologies, applications, challenges, and future aspects
Future smart cities are the key to fulfilling the ever-growing demands of citizens. Information
and communication advancements will empower better administration of accessible …
and communication advancements will empower better administration of accessible …
A 64-tile 2.4-Mb in-memory-computing CNN accelerator employing charge-domain compute
Large-scale matrix-vector multiplications, which dominate in deep neural networks (DNNs),
are limited by data movement in modern VLSI technologies. This paper addresses data …
are limited by data movement in modern VLSI technologies. This paper addresses data …
Multiple convolutional neural networks for multivariate time series prediction
Multivariate time series prediction, with a profound impact on human social life, has been
attracting growing interest in machine learning research. However, the task of time series …
attracting growing interest in machine learning research. However, the task of time series …
Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting
Y Wang, L Wang, F Yang, W Di, Q Chang - Information Sciences, 2021 - Elsevier
Abstract The Elman neural network (ElmanNN) is well-known for its capability of processing
dynamic information, which has led to successful applications in stock forecasting. In this …
dynamic information, which has led to successful applications in stock forecasting. In this …
Attention-based bidirectional GRU networks for efficient HTTPS traffic classification
Distributed and pervasive web services have become a major platform for sharing
information. However, the hypertext transfer protocol secure (HTTPS), which is a crucial web …
information. However, the hypertext transfer protocol secure (HTTPS), which is a crucial web …
GPU-accelerated compression and visualization of large-scale vessel trajectories in maritime IoT industries
Y Huang, Y Li, Z Zhang, RW Liu - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The automatic identification system (AIS), an automatic vessel-tracking system, has been
widely adopted to perform intelligent traffic management and collision avoidance services in …
widely adopted to perform intelligent traffic management and collision avoidance services in …
Resampling ensemble model based on data distribution for imbalanced credit risk evaluation in P2P lending
K Niu, Z Zhang, Y Liu, R Li - Information Sciences, 2020 - Elsevier
The misclassification of loan applicants by credit scoring model is one of the main factors
causing the loss of investors' profits in P2P lending. Class imbalance of credit data is a main …
causing the loss of investors' profits in P2P lending. Class imbalance of credit data is a main …
Efficient scientific workflow scheduling for deadline-constrained parallel tasks in cloud computing environments
Data centers for cloud computing must accommodate numerous parallel task executions
simultaneously. Therefore, data centers have many virtual machines (VMs). Minimizing the …
simultaneously. Therefore, data centers have many virtual machines (VMs). Minimizing the …
An improved adaptive genetic algorithm based on DV-Hop for locating nodes in wireless sensor networks
A Ouyang, Y Lu, Y Liu, M Wu, X Peng - Neurocomputing, 2021 - Elsevier
The localization problem of unknown nodes in wireless sensor networks (WSN) has drawn
increasing scholarly attention along together the popularity of meta-heuristic algorithms. To …
increasing scholarly attention along together the popularity of meta-heuristic algorithms. To …
Modeling temporal patterns with dilated convolutions for time-series forecasting
Time-series forecasting is an important problem across a wide range of domains. Designing
accurate and prompt forecasting algorithms is a non-trivial task, as temporal data that arise …
accurate and prompt forecasting algorithms is a non-trivial task, as temporal data that arise …