Jiachang Liu^1,*, Zhengwei Huang², Junfeng Xiang¹, Lu Liu¹, Manlin Hu¹

Energy Engineering, Vol.121, No.11, pp. 3461-3486, 2024, DOI:10.32604/ee.2024.054514 - 21 October 2024

Abstract To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance, this paper proposes a seasonal short-term load combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model. Specifically, the characteristics of load components are analyzed for different seasons, and the corresponding models are established. First, the improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) method is employed to decompose the system load for all four seasons, and the new sequence is obtained through reconstruction based on the… More >

Ting Cai¹, Chun Ye¹, Zhiwei Ye^1,*, Ziyuan Chen¹, Mengqing Mei¹, Haichao Zhang¹, Wanfang Bai², Peng Zhang³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1157-1175, 2024, DOI:10.32604/cmc.2024.055080 - 15 October 2024

Abstract The world produces vast quantities of high-dimensional multi-semantic data. However, extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging. Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features. The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection, because of its simplicity, efficiency, and similarity to reinforcement learning. Nevertheless, existing methods do not consider crucial correlation information, such as dynamic redundancy and label correlation. To tackle these concerns, the paper proposes a More >

Abdur Rashid Sangi^1,*, Satish Anamalamudi², Mohammed S. Alkatheiri³, Murali Krishna Enduri², Anil Carie², Mohammed A. Alqarni⁴

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2217-2234, 2023, DOI:10.32604/cmc.2023.038305 - 30 August 2023

Abstract Vehicular Adhoc Networks (VANETs) enable vehicles to act as mobile nodes that can fetch, share, and disseminate information about vehicle safety, emergency events, warning messages, and passenger infotainment. However, the continuous dissemination of information from vehicles and their one-hop neighbor nodes, Road Side Units (RSUs), and VANET infrastructures can lead to performance degradation of VANETs in the existing host-centric IP-based network. Therefore, Information Centric Networks (ICN) are being explored as an alternative architecture for vehicular communication to achieve robust content distribution in highly mobile, dynamic, and error-prone domains. In ICN-based Vehicular-IoT networks, consumer mobility is… More >

V. S. Vaisakhi^1,*, D. Surendran²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 181-193, 2023, DOI:10.32604/csse.2023.032514 - 20 January 2023

Abstract In signal processing and communication systems, digital filters are widely employed. In some circumstances, the reliability of those systems is crucial, necessitating the use of fault tolerant filter implementations. Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters. As technology advances, more complicated systems with several filters become possible. Some of the filters in those complicated systems frequently function in parallel, for example, by applying the same filter to various input signals. Recently, a simple strategy for achieving fault tolerance that takes advantage… More >

Jianjun Yao^*, Chen Qian, Yikun Zhang, Geyang Yu

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1283-1303, 2023, DOI:10.32604/cmes.2022.021328 - 31 August 2022

Abstract The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space, low power consumption, and excellent flexibility. However, the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining. In the process of ship construction, the performance of the parts’ protective coating needs to be machined to meet the Performance Standard of Protective Coatings (PSPC). The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle, greatly reducing machining quality and efficiency. There… More >

Jinglin Liang^1,2, Qian Sun^1,2,*, Xiaoyi Wang^3,2, Jiping Xu^1,2, Huiyan Zhang^1,2, Li Wang^1,2, Jiabin Yu^1,2, Jing Li⁴, Ruichao Wang⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5459-5471, 2022, DOI:10.32604/cmc.2022.029362 - 28 July 2022

Abstract Underwater sensor networks have important application value in the fields of water environment data collection, marine environment monitoring and so on. It has some characteristics such as low available bandwidth, large propagation delays and limited energy, which bring new challenges to the current researches. The research on coverage control of underwater sensor networks is the basis of other related researches. A good sensor node coverage control method can effectively improve the quality of water environment monitoring. Aiming at the problem of high dynamics and uncertainty of monitoring targets, the random events level are divided into… More >

B. Venkatesan^1,*, S. Chitra²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1603-1615, 2022, DOI:10.32604/iasc.2022.026049 - 25 May 2022

Abstract The cloud storage is essential environment for users to access high confidential data. Every single data is most valued by users. If we count, day by day information as well as, memory storage are increasing gradually. Cost of memory will increase when data increases with demand for storage. At present data duplication or redundant data storing in the cloud became hard for storage provider. Also, it makes security issue if repeated data from various users stored in the server. It makes data duplication, which is very efficient for intruders. Also, when same data stored in… More >

T. Vetriselvi^1,*, J. Albert Mayan², K. V. Priyadharshini³, K. Sathyamoorthy⁴, S. Venkata Lakshmi⁵, P. Vishnu Raja⁶

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1537-1551, 2022, DOI:10.32604/iasc.2022.025235 - 25 May 2022

Abstract Recently, the bounteous amount of data/information has been available on the Internet which makes it very complicated to the customers to calculate the preferred data. Because the huge amount of data in a system is mandated to discover the most proper data from the corpus. Content summarization selects and extracts the related sentence depends upon the calculation of the score and rank of the corpus. Automatic content summarization technique translates from the higher corpus into smaller concise description. This chooses the very important level of the texts and implements the complete statistics summary. This paper… More >

Bobbinpreet¹, Sultan Aljahdali^2,*, Tripti Sharma¹, Bhawna Goyal¹, Ayush Dogra³, Shubham Mahajan⁴, Amit Kant Pandit⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4771-4787, 2022, DOI:10.32604/cmc.2022.023150 - 21 April 2022

Abstract In recent times, the images and videos have emerged as one of the most important information source depicting the real time scenarios. Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane. The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition. One of the application fields pertains to detection of diseases occurring in the plants, which are destroying the widespread fields. Traditionally the disease detection… More >

B. Padmavathi^1,2,*, B. Muthukumar³

Computer Systems Science and Engineering, Vol.43, No.1, pp. 119-139, 2022, DOI:10.32604/csse.2022.021431 - 23 March 2022

Abstract Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various researchers. However, certain limitations need to be addressed efficiently. The provisioning of detection mechanism with learning approaches provides a better solution more broadly by saluting multi-objective constraints. The bots’ patterns or features over the network have to be analyzed in both linear and non-linear manner. The linear and non-linear features are composed of high-level and low-level features. The collected features are maintained over the Bag of Features (BoF) where the most influencing features are collected and provided into the… More >