Elif Çaloğlu Büyükselçuk^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 715-746, 2024, DOI:10.32604/cmc.2024.052509

Abstract Industrial Internet of Things (IIoT) service providers have become increasingly important in the manufacturing industry due to their ability to gather and process vast amounts of data from connected devices, enabling manufacturers to improve operational efficiency, reduce costs, and enhance product quality. These platforms provide manufacturers with real-time visibility into their production processes and supply chains, allowing them to optimize operations and make informed decisions. In addition, IIoT service providers can help manufacturers create new revenue streams through the development of innovative products and services and enable them to leverage the benefits of emerging technologies… More >

Kenian Wang^1,2,*, Yuan Hong^1,2, Chunxiao Li²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1123-1142, 2024, DOI:10.32604/cmc.2024.052088

Abstract With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system… More >

Phi-Hung Nguyen^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1655-1675, 2024, DOI:10.32604/cmc.2024.050713

Abstract This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets (SFSs) and Z-Numbers (SFZs). A novel group expert consensus technique, the PHI model, is developed to address the inherent limitations of both SFSs and the traditional Delphi technique, particularly in uncertain, complex scenarios. In such contexts, the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations. This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers, encompassing weighted geometric and arithmetic operators alongside fully developed operators… More >

Chia-Nan Wang, Thuy-Duong Thi Pham^*, Nhat-Luong Nhieu

Energy Engineering, Vol.121, No.8, pp. 2039-2064, 2024, DOI:10.32604/ee.2024.050224

Abstract Geothermal energy is considered a renewable, environmentally friendly, especially carbon-free, sustainable energy source that can solve the problem of climate change. In general, countries with geothermal energy resources are the ones going through the ring of fire. Therefore, not every country is lucky enough to own this resource. As a country with 117 active volcanoes and within the world’s ring of fire, it is a country whose geothermal resources are estimated to be about 40% of the world’s geothermal energy potential. However, the percentage used compared to the geothermal potential is too small. Therefore, this… More >

Tiezhou Wu, Yukan Zhang^*

Energy Engineering, Vol.121, No.8, pp. 2231-2255, 2024, DOI:10.32604/ee.2024.049883

Abstract In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs, a new multilayer equilibrium topology is designed in this paper. The structure adopts a hierarchical structure design, which includes intra-group equilibrium, primary inter-group equilibrium and secondary inter-group equilibrium. This structure greatly increases the number of equilibrium paths for lithium-ion batteries, thus shortening the time required for equilibrium, and improving the overall efficiency. In terms of control strategy, fuzzy logic control (FLC) is chosen to control the size of the equilibrium current during the equilibrium process. We… More >

M. Navya Pratyusha, Ranjan Kumar^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2957-2976, 2024, DOI:10.32604/cmes.2024.051581

Abstract In the real world, one of the most common problems in project management is the unpredictability of resources and timelines. An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach, often known as neutrosophic logic. Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number. This innovative approach evaluates the inherent uncertainty in project durations of the planning phase, which enhances the potential significance of the decision-making process in the project. Our proposed method, for the first time… More >

Navaneethakrishnan Suganthi Keerthana Devi¹, Samayan Narayanamoorthy¹, Thirumalai Nallasivan Parthasarathy¹, Chakkarapani Sumathi Thilagasree², Dragan Pamucar^3,4,*, Vladimir Simic^5,6, Hasan Dinçer^7,8, Serhat Yüksel^7,8

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2665-2687, 2024, DOI:10.32604/cmes.2024.050954

Abstract Food Waste (FW) is a pressing environmental concern that affects every country globally. About one-third of the food that is produced ends up as waste, contributing to the carbon footprint. Hence, the FW must be properly treated to reduce environmental pollution. This study evaluates a few available Food Waste Treatment (FWT) technologies, such as anaerobic digestion, composting, landfill, and incineration, which are widely used. A Bipolar Picture Fuzzy Set (BPFS) is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model. A novel Criteria Importance Through… More >

Jiqiang Chen, Ranran Han, Dongqing Zhang, Litao Ma^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5067-5082, 2024, DOI:10.32604/cmc.2024.051494

Abstract Imbalanced datasets are common in practical applications, and oversampling methods using fuzzy rules have been shown to enhance the classification performance of imbalanced data by taking into account the relationship between data attributes. However, the creation of fuzzy rules typically depends on expert knowledge, which may not fully leverage the label information in training data and may be subjective. To address this issue, a novel fuzzy rule oversampling approach is developed based on the learning vector quantization (LVQ) algorithm. In this method, the label information of the training data is utilized to determine the antecedent… More >

Djeldjli Halima^1,*, Benatiallah Djelloul¹, Ghasri Mehdi², Tanougast Camel³, Benatiallah Ali⁴, Benabdelkrim Bouchra¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002

Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract

Yi-Chun Lai¹, Shu-Yin Chiang², Yao-Chiang Kan³, Hsueh-Chun Lin^4,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3783-3803, 2024, DOI:10.32604/cmc.2024.050376

Abstract Artificial intelligence (AI) technology has become integral in the realm of medicine and healthcare, particularly in human activity recognition (HAR) applications such as fitness and rehabilitation tracking. This study introduces a robust coupling analysis framework that integrates four AI-enabled models, combining both machine learning (ML) and deep learning (DL) approaches to evaluate their effectiveness in HAR. The analytical dataset comprises 561 features sourced from the UCI-HAR database, forming the foundation for training the models. Additionally, the MHEALTH database is employed to replicate the modeling process for comparative purposes, while inclusion of the WISDM database, renowned… More > Graphic Abstract