Tsu-Yang Wu^1,2, Haonan Li², Saru Kumari³, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 19-46, 2024, DOI:10.32604/cmc.2024.048347

Abstract Hyperspectral image classification stands as a pivotal task within the field of remote sensing, yet achieving high-precision classification remains a significant challenge. In response to this challenge, a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm (AFLA-SCNN) is proposed. The Adaptive Fick’s Law Algorithm (AFLA) constitutes a novel metaheuristic algorithm introduced herein, encompassing three new strategies: Adaptive weight factor, Gaussian mutation, and probability update policy. With adaptive weight factor, the algorithm can adjust the weights according to the change in the number of iterations to improve the performance of the algorithm. Gaussian mutation helps the algorithm avoid… More >

Yuejiao Wang, Zhong Ma^*, Chaojie Yang, Yu Yang, Lu Wei

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 819-836, 2024, DOI:10.32604/cmc.2024.047108

Abstract The quantization algorithm compresses the original network by reducing the numerical bit width of the model, which improves the computation speed. Because different layers have different redundancy and sensitivity to data bit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determine the optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantization can effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In this paper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bit width is proposed,… More >

Xianwei Jiang¹, Yanqiong Zhang^1,*, Juan Lei¹, Yudong Zhang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1-40, 2024, DOI:10.32604/cmes.2024.047649

Abstract Research on Chinese Sign Language (CSL) provides convenience and support for individuals with hearing impairments to communicate and integrate into society. This article reviews the relevant literature on Chinese Sign Language Recognition (CSLR) in the past 20 years. Hidden Markov Models (HMM), Support Vector Machines (SVM), and Dynamic Time Warping (DTW) were found to be the most commonly employed technologies among traditional identification methods. Benefiting from the rapid development of computer vision and artificial intelligence technology, Convolutional Neural Networks (CNN), 3D-CNN, YOLO, Capsule Network (CapsNet) and various deep neural networks have sprung up. Deep Neural Networks (DNNs) and their derived… More >

Sang-min Lee, Namgi Kim^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1897-1914, 2024, DOI:10.32604/cmc.2023.046346

Abstract Recommendation Information Systems (RIS) are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet. Graph Convolution Network (GCN) algorithms have been employed to implement the RIS efficiently. However, the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process. To address this issue, we propose a Weighted Forwarding method using the GCN (WF-GCN) algorithm. The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning. By applying the WF-GCN… More >

Yaoyao Du, Xiangkui Jiang^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 303-327, 2024, DOI:10.32604/cmc.2023.046068

Abstract To address the challenges of high complexity, poor real-time performance, and low detection rates for small target vehicles in existing vehicle object detection algorithms, this paper proposes a real-time lightweight architecture based on You Only Look Once (YOLO) v5m. Firstly, a lightweight upsampling operator called Content-Aware Reassembly of Features (CARAFE) is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles, reducing the missed detection rate and false detection rate. Secondly, a new prediction layer for tiny targets is added, and the feature fusion network is redesigned to enhance the… More >

Abdul Rehman, Dongsun Kim^*, Anand Paul

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2289-2307, 2023, DOI:10.32604/cmc.2023.036435

Abstract Disasters such as conflagration, toxic smoke, harmful gas or chemical leakage, and many other catastrophes in the industrial environment caused by hazardous distance from the peril are frequent. The calamities are causing massive fiscal and human life casualties. However, Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social fiasco. The authors have proposed an early fire detection system uses machine and/or deep learning algorithms. The article presents an Intelligent Industrial Monitoring System (IIMS) and introduces an Industrial Smart Social Agent (ISSA) in the Industrial SIoT (ISIoT) paradigm. The proffered ISSA empowers smart… More >

Shumin Sun¹, Peng Yu¹, Jiawei Xing¹, Yan Cheng¹, Song Yang¹, Qian Ai^2,*

Energy Engineering, Vol.120, No.12, pp. 2761-2782, 2023, DOI:10.32604/ee.2023.042635

Abstract Wind power prediction is very important for the economic dispatching of power systems containing wind power. In this work, a novel short-term wind power prediction method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and (long short-term memory) LSTM neural network is proposed and studied. First, the original data is prepossessed including removing outliers and filling in the gaps. Then, the random forest algorithm is used to sort the importance of each meteorological factor and determine the input climate characteristics of the forecast model. In addition, this study conducts seasonal classification of the annual data where… More >

Dun Cao¹, Jia Ru¹, Jian Qin¹, Amr Tolba², Jin Wang¹, Min Zhu^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1365-1384, 2024, DOI:10.32604/cmes.2023.030260

Abstract Internet of Vehicles (IoV) is a new system that enables individual vehicles to connect with nearby vehicles, people, transportation infrastructure, and networks, thereby realizing a more intelligent and efficient transportation system. The movement of vehicles and the three-dimensional (3D) nature of the road network cause the topological structure of IoV to have the high space and time complexity. Network modeling and structure recognition for 3D roads can benefit the description of topological changes for IoV. This paper proposes a 3D general road model based on discrete points of roads obtained from GIS. First, the constraints imposed by 3D roads on… More >

A. Aldo Tenis^*, R. Santhosh

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2625-2641, 2023, DOI:10.32604/csse.2023.036626

Abstract The social engineering cyber-attack is where culprits mislead the users by getting the login details which provides the information to the evil server called phishing. The deep learning approaches and the machine learning are compared in the proposed system for presenting the methodology that can detect phishing websites via Uniform Resource Locator (URLs) analysis. The legal class is composed of the home pages with no inclusion of login forms in most of the present modern solutions, which deals with the detection of phishing. Contrarily, the URLs in both classes from the login page due, considering the representation of a real… More >

Wafa F. Alfwzan¹, Dumitru Baleanu^2,3,4, Fazal Dayan^5,*, Sami Ullah⁵, Nauman Ahmed^4,6, Muhammad Rafiq^7,8, Ali Raza^4,9

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1909-1924, 2023, DOI:10.32604/iasc.2023.039249

Abstract A susceptible, exposed, infectious, quarantined and recovered (SEIQR) model with fuzzy parameters is studied in this work. Fuzziness in the model arises due to the different degrees of susceptibility, exposure, infectivity, quarantine and recovery among the computers under consideration due to the different sizes, models, spare parts, the surrounding environments of these PCs and many other factors like the resistance capacity of the individual PC against the virus, etc. Each individual PC has a different degree of infectivity and resistance against infection. In this scenario, the fuzzy model has richer dynamics than its classical counterpart in epidemiology. The reproduction number… More >