Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (89)
  • Open Access

    ARTICLE

    Fuzzy with Metaheuristics Based Routing for Clustered Wireless Sensor Networks

    Ashit Kumar Dutta1,*, Yasser Albagory2, Majed Alsanea3, Abdul Rahaman Wahab Sait4, Hazim Saleh AlRawashdeh5

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 367-380, 2023, DOI:10.32604/iasc.2023.027076

    Abstract Wireless sensor network (WSN) plays a vital part in real time tracking and data collection applications. WSN incorporates a set of numerous sensor nodes (SNs) commonly utilized to observe the target region. The SNs operate using an inbuilt battery and it is not easier to replace or charge it. Therefore, proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN. In this study, an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection (TFL-BOARS) has been developed for clustered WSN. The TFL-BOARS technique intends to optimally select the cluster heads (CHs) and… More >

  • Open Access

    ARTICLE

    Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

    Yujun Su1, Xianghao Gao2, Hong Qian2, Xiaoyan Su2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 201-214, 2022, DOI:10.32604/cmes.2022.020541

    Abstract Human Reliability Analysis (HRA) is an important part in safety assessment of a large complex system. Human Cognitive Reliability (HCR) model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time, which is widely used in HRA. In the application of this method, cognitive patterns of humans are required to be considered and classified, and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain. How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy… More >

  • Open Access

    ARTICLE

    Optimal Decision-Making of Trans-Provincial Electricity Market Subjects with Risks under Renewable Portfolio Standards

    Hui Wang, Yishu Chen*, Zichao Wu, Haocheng Xu

    Energy Engineering, Vol.119, No.3, pp. 1141-1167, 2022, DOI:10.32604/ee.2022.016151

    Abstract

    The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects. Therefore, it is beneficial to optimize the interests of each of these subjects, considering the unpredictable risks of renewable energy under the renewable portfolio standards (RPS) and researching their effects on the optimal decision-making of trans-provincial electricity market multi-subjects. First, we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricity market multi-subjects. Then, under the RPS, we construct a multi-subject… More >

  • Open Access

    ARTICLE

    Internal Validity Index for Fuzzy Clustering Based on Relative Uncertainty

    Refik Tanju Sirmen1,*, Burak Berk Üstündağ2

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2909-2926, 2022, DOI:10.32604/cmc.2022.023947

    Abstract Unsupervised clustering and clustering validity are used as essential instruments of data analytics. Despite clustering being realized under uncertainty, validity indices do not deliver any quantitative evaluation of the uncertainties in the suggested partitionings. Also, validity measures may be biased towards the underlying clustering method. Moreover, neglecting a confidence requirement may result in over-partitioning. In the absence of an error estimate or a confidence parameter, probable clustering errors are forwarded to the later stages of the system. Whereas, having an uncertainty margin of the projected labeling can be very fruitful for many applications such as machine learning. Herein, the validity… More >

  • Open Access

    ARTICLE

    Dynamic Sliding Mode Backstepping Control for Vertical Magnetic Bearing System

    Wei-Lung Mao1,*, Yu-Ying Chiu1, Chao-Ting Chu2, Bing-Hong Lin1, Jian-Jie Hung3

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 923-936, 2022, DOI:10.32604/iasc.2022.019555

    Abstract Electromagnets are commonly used as support for machine components and parts in magnetic bearing systems (MBSs). Compared with conventional mechanical bearings, the magnetic bearings have less noise, friction, and vibration, but the magnetic force has a highly nonlinear relationship with the control current and the air gap. This research presents a dynamic sliding mode backstepping control (DSMBC) designed to track the height position of modeless vertical MBS. Because MBS is nonlinear with model uncertainty, the design of estimator should be able to solve the lumped uncertainty. The proposed DSMBC controller can not only stabilize the nonlinear system under mismatched uncertainties,… More >

  • Open Access

    ARTICLE

    Ensembles of Deep Learning Framework for Stomach Abnormalities Classification

    Talha Saeed, Chu Kiong Loo*, Muhammad Shahreeza Safiruz Kassim

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4357-4372, 2022, DOI:10.32604/cmc.2022.019076

    Abstract

    Abnormalities of the gastrointestinal tract are widespread worldwide today. Generally, an effective way to diagnose these life-threatening diseases is based on endoscopy, which comprises a vast number of images. However, the main challenge in this area is that the process is time-consuming and fatiguing for a gastroenterologist to examine every image in the set. Thus, this led to the rise of studies on designing AI-based systems to assist physicians in the diagnosis. In several medical imaging tasks, deep learning methods, especially convolutional neural networks (CNNs), have contributed to the state-of-the-art outcomes, where the complicated nonlinear relation between target classes and… More >

  • Open Access

    ARTICLE

    Neutrosophic Mathematical Programming for Optimization of Multi-Objective Sustainable Biomass Supply Chain Network Design

    Mohammad Fallah*, Hamed Nozari

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 927-951, 2021, DOI:10.32604/cmes.2021.017511

    Abstract In this paper, a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method. In this method, for each objective function of the problem, three functions of truth membership, non-determination and falsehood are considered. Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network, the amount of greenhouse gas emissions, the number of potential people hired and the time of product transfer along the supply chain network. To achieve the stated objective functions, strategic decisions such as locating potential facilities and tactical decisions such as optimal product flow… More >

  • Open Access

    ARTICLE

    Investigation on the Indeterminate Information of Rock Joint Roughness through a Neutrosophic Number Approach

    Changshuo Wang1, Liangqing Wang2,*, Shigui Du1, Jun Ye1,3, Rui Yong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 973-991, 2021, DOI:10.32604/cmes.2021.017453

    Abstract To better estimate the rock joint shear strength, accurately determining the rock joint roughness coefficient (JRC) is the first step faced by researchers and engineers. However, there are incomplete, imprecise, and indeterminate problems during the process of calculating the JRC. This paper proposed to investigate the indeterminate information of rock joint roughness through a neutrosophic number approach and, based on this information, reported a method to capture the incomplete, uncertain, and imprecise information of the JRC in uncertain environments. The uncertainties in the JRC determination were investigated by the regression correlations based on commonly used statistical parameters, which demonstrated the… More >

  • Open Access

    ARTICLE

    Two-Stage Production Planning Under Stochastic Demand: Case Study of Fertilizer Manufacturing

    Chia-Nan Wang1, Shao-Dong Syu1,2,*, Chien-Chang Chou3, Viet Tinh Nguyen4, Dang Van Thuy Cuc5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1195-1207, 2022, DOI:10.32604/cmc.2022.019890

    Abstract Agriculture is a key facilitator of economic prosperity and nourishes the huge global population. To achieve sustainable agriculture, several factors should be considered, such as increasing nutrient and water efficiency and/or improving soil health and quality. Using fertilizer is one of the fastest and easiest ways to improve the quality of nutrients inland and increase the effectiveness of crop yields. Fertilizer supplies most of the necessary nutrients for plants, and it is estimated that at least 30%–50% of crop yields is attributable to commercial fertilizer nutrient inputs. Fertilizer is always a major concern in achieving sustainable and efficient agriculture. Applying… More >

  • Open Access

    ARTICLE

    Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

    Mohamed Abdel-Basset1, Ahmed Sleem1, Asmaa Atef1, Yunyoung Nam2,*, Mohamed Abouhawwash3,4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 847-874, 2022, DOI:10.32604/cmc.2022.017106

    Abstract Project scheduling is a key objective of many models and is the proposed method for project planning and management. Project scheduling problems depend on precedence relationships and resource constraints, in addition to some other limitations for achieving a subset of goals. Project scheduling problems are dependent on many limitations, including limitations of precedence relationships, resource constraints, and some other limitations for achieving a subset of goals. Deterministic project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required, which are known and stable during the implementation process. The concept… More >

Displaying 31-40 on page 4 of 89. Per Page