Hongjun Zhang^1,2, Zeyu Zhang³, Yilong Ruan⁴, Hao Ye^5,6, Peng Li^1,*, Desheng Shi¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1409-1432, 2024, DOI:10.32604/cmc.2024.055406 - 15 October 2024

Abstract The scale and complexity of big data are growing continuously, posing severe challenges to traditional data processing methods, especially in the field of clustering analysis. To address this issue, this paper introduces a new method named Big Data Tensor Multi-Cluster Distributed Incremental Update (BDTMCDIncreUpdate), which combines distributed computing, storage technology, and incremental update techniques to provide an efficient and effective means for clustering analysis. Firstly, the original dataset is divided into multiple sub-blocks, and distributed computing resources are utilized to process the sub-blocks in parallel, enhancing efficiency. Then, initial clustering is performed on each sub-block… More >

Shilpa Suman¹, Abhishek Rawat^2,*, Anil Kumar³, S. K. Tiwari⁴

Revue Internationale de Géomatique, Vol.33, pp. 363-381, 2024, DOI:10.32604/rig.2024.053981 - 18 September 2024

Abstract In this study, the impact of the training sample selection method on the performance of fuzzy-based Possibilistic c-means (PCM) and Noise Clustering (NC) classifiers were examined and mapped the cumin and fennel rabi crop. Two training sample selection approaches that have been investigated in this study are “mean” and “individual sample as mean”. Both training sample techniques were applied to the PCM and NC classifiers to classify the two indices approach. Both approaches have been studied to decrease spectral information in temporal data processing. The Modified Soil Adjusted Vegetation Index 2 (MSAVI-2) and Class-Based Sensor… More >

Xianghui Hu¹, Yiming Tang^2,3, Witold Pedrycz^3,4, Jiuchuan Jiang^5,*, Yichuan Jiang^1,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4917-4945, 2024, DOI:10.32604/cmc.2024.054775 - 12 September 2024

Abstract Traditional Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) clustering algorithms are data-driven, and their objective function minimization process is based on the available numeric data. Recently, knowledge hints have been introduced to form knowledge-driven clustering algorithms, which reveal a data structure that considers not only the relationships between data but also the compatibility with knowledge hints. However, these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself; they require the assistance of evaluation indices. Moreover, knowledge hints are usually used as part of the data structure (directly replacing some clustering centers),… More >

Syed Kamran Haider^1,2, Abbas Ahmed², Noman Mujeeb Khan², Ali Nauman^3,*, Sung Won Kim^3,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4085-4110, 2024, DOI:10.32604/cmc.2024.052997 - 12 September 2024

Abstract In recent advancements within wireless sensor networks (WSN), the deployment of unmanned aerial vehicles (UAVs) has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network functionality. This research introduces a sophisticated framework, driven by computational intelligence, that merges clustering techniques with UAV mobility to refine routing strategies in WSNs. The proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads (CHs). This system is primarily aimed at reducing energy consumption through meticulously planned routing and path determination. Employing a greedy algorithm More >

R. Mahaveerakannan¹, Thanarajan Tamilvizhi^2,*, Sonia Jenifer Rayen³, Osamah Ibrahim Khalaf⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3945-3966, 2024, DOI:10.32604/cmc.2024.051611 - 12 September 2024

Abstract The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content. In light of the data-centric aspect of contemporary communication, the information-centric network (ICN) paradigm offers hope for a solution by emphasizing content retrieval by name instead of location. If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things (IoT) devices, then effective caching solutions will be required to maximize network throughput and minimize the use of resources. Hence, an ICN-based Cooperative Caching (ICN-CoC) technique has been used to select… More >

Mingxuan Chen¹, Jun Jia², Baoping Zhang¹, Leiyan Han³, Mengbo Ji^3,4, Zhangtao Yu¹, Dongfang Li¹, Wenyong Wang¹, Hongjing Jia¹, Huachi Xu^2,*

Energy Engineering, Vol.121, No.10, pp. 3055-3074, 2024, DOI:10.32604/ee.2024.051524 - 11 September 2024

Abstract The rise in hydrogen production powered by renewable energy is driving the field toward the adoption of systems comprising multiple alkaline water electrolyzers. These setups present various operational modes: independent operation and multi-electrolyzer parallelization, each with distinct advantages and challenges. This study introduces an innovative configuration that incorporates a mutual lye mixer among electrolyzers, establishing a weakly coupled system that combines the advantages of two modes. This approach enables efficient heat utilization for faster hot-startup and maintains heat conservation post-lye interconnection, while preserving the option for independent operation after decoupling. A specialized thermal exchange model… More >

V. G. Saranya^*, S. Karthik

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825 - 20 August 2024

Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

Jiaxin Qiao¹, Yuchen Hao², Yingqi Liao³, Fang Liang³, Jing Bian^1,*

Energy Engineering, Vol.121, No.9, pp. 2655-2680, 2024, DOI:10.32604/ee.2024.049509 - 19 August 2024

Abstract The massive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations. To accurately assess the flexible regulation capabilities of distribution stations, a multi-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics, considering different geographical locations, coverage areas, and response capabilities. Firstly, the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed, and a resource regulation capability model is established to quantify the adjustable range of different regulation resources. On… More >

Liang Zhu¹, Junyang Liu¹, Chen Hu¹, Yanli Zhi², Yupeng Liu^3,*

Energy Engineering, Vol.121, No.9, pp. 2639-2653, 2024, DOI:10.32604/ee.2024.041441 - 19 August 2024

Abstract Studying user electricity consumption behavior is crucial for understanding their power usage patterns. However, the traditional clustering methods fail to identify emerging types of electricity consumption behavior. To address this issue, this paper introduces a statistical analysis of clusters and evaluates the set of indicators for power usage patterns. The fuzzy C-means clustering algorithm is then used to analyze 6 months of electricity consumption data in 2017 from energy storage equipment, agricultural drainage irrigation, port shore power, and electric vehicles. Finally, the proposed method is validated through experiments, where the Davies-Bouldin index and profile coefficient More >

Hina Gul¹, Sana Ullah¹, Ki-Il Kim^2,*, Farman Ali³

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1831-1850, 2024, DOI:10.32604/cmc.2024.052841 - 15 August 2024

Abstract The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super… More >