Shanshan Wang^1,2,3, Quan Yuan¹, Weiwei Tan¹, Tengfei Yang¹, Liang Zeng^1,2,3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3057-3075, 2023, DOI:10.32604/cmc.2023.044807

Abstract Feature Selection (FS) is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy. However, due to the high dimensionality and complexity of the dataset, most optimization algorithms for feature selection suffer from a balance issue during the search process. Therefore, the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm (SCChOA) to address the feature selection problem. In this approach, firstly, a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm (SCA) and the Chimp Optimization Algorithm (ChOA), enabling a more effective search in the objective space. Secondly,… More >

Mustufa Haider Abidi^*, Hisham Alkhalefah, Muneer Khan Mohammed

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5367-5383, 2022, DOI:10.32604/cmc.2022.030018

Abstract In modern scenarios, Industry 4.0 entails invention with various advanced technology, and blockchain is one among them. Blockchains are incorporated to enhance privacy, data transparency as well as security for both large and small scale enterprises. Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively. However, because numerous devices and machines are involved, data security and privacy are always concerns. To achieve intelligence in Industry 4.0, blockchain technologies can overcome potential cybersecurity constraints. Nowadays, the blockchain and internet of things (IoT) are gaining more attention because of their favorable outcome… More >

Anas Al-Ragehi¹, Said Jadid Abdulkadir^1,2,*, Amgad Muneer^1,2, Safwan Sadeq³, Qasem Al-Tashi^4,5

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2169-2186, 2022, DOI:10.32604/cmc.2022.027885

Abstract Generative Adversarial Networks (GANs) are neural networks that allow models to learn deep representations without requiring a large amount of training data. Semi-Supervised GAN Classifiers are a recent innovation in GANs, where GANs are used to classify generated images into real and fake and multiple classes, similar to a general multi-class classifier. However, GANs have a sophisticated design that can be challenging to train. This is because obtaining the proper set of parameters for all models-generator, discriminator, and classifier is complex. As a result, training a single GAN model for different datasets may not produce satisfactory results. Therefore, this study… More >

Xin Zhang^*, Jinpeng Jiang, Haoran Zheng, Jihong Zhang

Energy Engineering, Vol.119, No.3, pp. 1117-1140, 2022, DOI:10.32604/ee.2022.017288

Abstract China consumes significant amount of natural gas in winter. The integrated community energy utilization system (ICEUS) cannot stabilize the output of electricity and heat if there is a shortage of natural gas. The operation cost of the system still needs improvement. An energy supply structure using garbage power as the core of ICEUS was established in the study. The optimal dispatching model of ICEUS was established using the regulating characteristic of the community load. The sine-cosine algorithm (SCA) based on nonlinear factors and segmented weight was presented to solve the optimal dispatching model of ICEUS. From the simulation results, compared… More >