M. A. A. Younis^1,*, Anas Quteishat^1,2

Computer Systems Science and Engineering, Vol.45, No.1, pp. 343-359, 2023, DOI:10.32604/csse.2023.029510

Abstract The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades, and the government has struggled to find a solution. In addition, Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040, including solar and wind turbines. Furthermore, the use of small-scale energy from wind devices has been on the rise in recent years. This upward trend is attributed to advancements in wind turbine technology, which have lowered the cost of energy from wind. To calculate… More >

Anas Quteishat^1,2,*, M. A. A. Younis²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2117-2134, 2023, DOI:10.32604/iasc.2023.029419

Abstract Renewable energy is created by renewable natural resources such as geothermal heat, sunlight, tides, rain, and wind. Energy resources are vital for all countries in terms of their economies and politics. As a result, selecting the optimal option for any country is critical in terms of energy investments. Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming. In the present work, the authors suggest fuzzy multi-characteristic decision-making approaches for renewable energy source selection, and fuzzy set theory is a valuable methodology for dealing with uncertainty in… More >

M. El Sayed^1,*, Wadia Faid Hassan Al-shameri¹, M. A. El Safty²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 865-879, 2022, DOI:10.32604/cmes.2022.020066

Abstract A soft, rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data. In the present work, we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space. These concepts are soft pre-rough equality, soft pre-rough inclusion, soft pre-rough belonging, soft predefinability, soft pre-internal lower, and soft pre-external lower. We study the properties of these concepts. Finally, we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses. In reality, the impact factors of Chikungunya’s medical infection were determined.… More >

Chia-Nan Wang, Tien–Lin Chao^*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2485-2494, 2022, DOI:10.32604/cmc.2022.026682

Abstract In many port capacity upgrade projects, choosing a supplier of equipment is a complicated decision, project managers must consider many criteria to choose a supplier to ensure the project is completed on time, optimal in terms of benefit and cost. Therefore, selecting the equipment supplier in this project is a multi-criteria decision-making process. The multi-criteria decision-making (MCDM) model is applied in many fields to select the optimal solution, but there are very few studies using the MCDM model to support project managers in evaluating and selecting optimal solutions in port capacity upgrade project. In this research, the authors combine Fuzzy… More >

Rui Yong^1,2,*, Jun Ye^1,2, Shigui Du^1,2, Aqin Zhu¹, Yingying Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 569-584, 2022, DOI:10.32604/cmes.2022.019509

Abstract The simplified neutrosophic number (SNN) can represent uncertain, imprecise, incomplete, and inconsistent information that exists in scientific, technological, and engineering fields. Hence, it is a useful tool for describing truth, falsity, and indeterminacy information in multiple attribute decision-making (MADM) problems. To suit decision makers’ preference selection, the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment. To solve this problem, this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility. First, we define the Aczel-Alsina operations of SNNs. Then, the Aczel-Alsina… More >

Nik Muhammad Farhan Hakim Nik Badrul Alam^1,2, Ku Muhammad Naim Ku Khalif^1,*, Nor Izzati Jaini¹

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 47-61, 2023, DOI:10.32604/iasc.2023.024660

Abstract Intuitionistic fuzzy numbers incorporate the membership and non-membership degrees. In contrast, Z-numbers consist of restriction components, with the existence of a reliability component describing the degree of certainty for the restriction. The combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers, namely intuitionistic Z-numbers (IZN). The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are characterized by the membership and non-membership functions, exhibiting the degree of the hesitancy of decision-makers. This paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.… More >

Faisal Al-Sharqi^1,2, Abd Ghafur Ahmad^1,*, Ashraf Al-Quran³

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 267-293, 2022, DOI:10.32604/cmes.2022.019684

Abstract A fuzzy system is a novel computing technique that accesses uncertain information by fuzzy representation. In the decision-making process, fuzzy system and soft computing are effective tools that are tolerant to imprecision, uncertainty, and partial truths. Evolutionary fuzzy systems have been developed with the appearance of interval fuzzy, dual fuzzy, hesitant fuzzy, neutrosophic, plithogenic representations, etc. Moreover, by capturing compound features and convey multi-dimensional data, complex numbers are utilized to generalize fuzzy and neutrosophic fuzzy sets. In this paper, a representation of neutrosophic soft expert systems based on the real and complex numbers in the interval form is proposed. The… More >

Mohammad Alamgeer¹, Saud S. Alotaibi², Shaha Al-Otaibi³, Nazik Alturki³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Ishfaq Yaseen⁴, Mohamed I. Eldesouki⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1159-1175, 2022, DOI:10.32604/cmc.2022.028275

Abstract Latest developments in computing and communication technologies are enabled the design of connected healthcare system which are mainly based on IoT and Edge technologies. Blockchain, data encryption, and deep learning (DL) models can be utilized to design efficient security solutions for IoT healthcare applications. In this aspect, this article introduces a Blockchain with privacy preserving image encryption and optimal deep learning (BPPIE-ODL) technique for IoT healthcare applications. The proposed BPPIE-ODL technique intends to securely transmit the encrypted medical images captured by IoT devices and performs classification process at the cloud server. The proposed BPPIE-ODL technique encompasses the design of dragonfly… More >

Thai Hoang Tuyet Nhi¹, Chia-Nan Wang¹, Nguyen Van Thanh^2,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4853-4865, 2022, DOI:10.32604/cmc.2022.026374

Abstract Vietnam is one of Southeast Asian countries with a rapid GDP growth rate, ranging from 6.5% to 7% annually, leading to an average increase in energy demand of 11% per year. This demand creates many new opportunities in the energy industry, especially renewable energy, to ensure sustainable development in the future for the country with applications of solar energy growing at the present, and other opportunities to expand in the future. In Vietnam, thanks to favorable weather, climate, terrain characteristics and many preferential support policies, there are many great opportunities in the field of solar energy exploitation and application. Location… More >

Rana Muhammad Zulqarnain¹, Imran Siddique², Aiyared Iampan³, Dumitru Baleanu^4,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1717-1750, 2022, DOI:10.32604/cmes.2022.019408

Abstract Interval-valued Pythagorean fuzzy so set (IVPFSS) is a generalization of the interval-valued intuitionistic fuzzy so set (IVIFSS) and interval-valued Pythagorean fuzzy set (IVPFS). The IVPFSS handled more uncertainty comparative to IVIFSS; it is the most signicant technique for explaining fuzzy information in the decision-making process. In this work, some novel operational laws for IVPFSS have been proposed. Based on presented operational laws, two innovative aggregation operators (AOs) have been developed such as interval-valued Pythagorean fuzzy so weighted average (IVPFSWA) and interval-valued Pythagorean fuzzy so weighted geometric (IVPFSWG) operators with their fundamental properties. A multi-attribute group decision-making (MAGDM) approach has been… More >