Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (100)
  • Open Access

    ARTICLE

    Power Aggregation Operators and Similarity Measures Based on Improved Intuitionistic Hesitant Fuzzy Sets and their Applications to Multiple Attribute Decision Making

    Tahir Mahmood1, Wajid Ali1, Zeeshan Ali1, Ronnason Chinram2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393 - 19 February 2021

    Abstract Intuitionistic hesitant fuzzy set (IHFS) is a mixture of two separated notions called intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), as an important technique to cope with uncertain and awkward information in realistic decision issues. IHFS contains the grades of truth and falsity in the form of the subset of the unit interval. The notion of IHFS was defined by many scholars with different conditions, which contain several weaknesses. Here, keeping in view the problems of already defined IHFSs, we will define IHFS in another way so that it becomes compatible with other… More >

  • Open Access

    REVIEW

    Medical Diagnosis Using Machine Learning: A Statistical Review

    Kaustubh Arun Bhavsar1, Jimmy Singla1, Yasser D. Al-Otaibi2, Oh-Young Song3,*, Yousaf Bin Zikria4, Ali Kashif Bashir5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 107-125, 2021, DOI:10.32604/cmc.2021.014604 - 12 January 2021

    Abstract Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted… More >

  • Open Access

    ARTICLE

    An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment

    Ayesha Jabeen1, Sitara Afzal1, Muazzam Maqsood1, Irfan Mehmood2, Sadaf Yasmin1, Muhammad Tabish Niaz3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1191-1206, 2021, DOI:10.32604/cmc.2021.014598 - 12 January 2021

    Abstract Stock market forecasting is an important research area, especially for better business decision making. Efficient stock predictions continue to be significant for business intelligence. Traditional short-term stock market forecasting is usually based on historical market data analysis such as stock prices, moving averages, or daily returns. However, major events’ news also contains significant information regarding market drivers. An effective stock market forecasting system helps investors and analysts to use supportive information regarding the future direction of the stock market. This research proposes an efficient model for stock market prediction. The current proposed study explores the More >

  • Open Access

    ARTICLE

    Fuzzy Based Decision-Making Approach for Estimating Usable-Security of Healthcare Web Applications

    Fahad A. Alzahrani*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2599-2625, 2021, DOI:10.32604/cmc.2021.013124 - 28 December 2020

    Abstract Usability and security are often considered contradictory in nature. One has a negative impact on the other. In order to satisfy the needs of users with the security perspective, the relationship and trade-offs among security and usability must be distinguished. Security practitioners are working on developing new approaches that would help to secure healthcare web applications as well increase usability of the web applications. In the same league, the present research endeavour is premised on the usable-security of healthcare web applications. For a compatible blend of usability and security that would fulfill the users’ requirments,… More >

  • Open Access

    ARTICLE

    Multi Criteria Decision Making System for Parking System

    Manjur Kolhar*, Abdalla Alameen

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 101-116, 2021, DOI:10.32604/csse.2021.014915 - 23 December 2020

    Abstract System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques… More >

  • Open Access

    ARTICLE

    Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

    Abdullah Baz1,*, Hosam Alhakami2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1155-1174, 2021, DOI:10.32604/cmc.2020.013215 - 26 November 2020

    Abstract The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to… More >

  • Open Access

    ARTICLE

    Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

    Changli Lu1, Ming Zhao1,2, Imran Khan3, Peerapong Uthansakul4,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1511-1528, 2021, DOI:10.32604/cmc.2020.012556 - 26 November 2020

    Abstract The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia. For the sustainable development of maritime transport, International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020. With the approaching of the stipulated implementation date, shipowners need to adopt scientific methods to make decision on low sulfur fuel. In this study, we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel. For this purpose, the… More >

  • Open Access

    ARTICLE

    Pediatric cystoscopy of male urethral strictures: an accurate and useful preoperative surgical decision making tool

    Gregory P. Murphy1, Kushan D. Radadia1, Jonathan Weese1, Cooper R. Benson2, Niraj Badhiwala1, Alethea Paradis1, Joel Vetter1, Steven B. Brandes2

    Canadian Journal of Urology, Vol.27, No.3, pp. 10228-10232, 2020

    Abstract Introduction: To evaluate flexible pediatric cystoscopy (FPC) as an adjunctive procedure to retrograde urethrography (RUG) and voiding cystourethrography (VCUG) in the preoperative setting for male urethral strictures. Since imaging interpretation of stricture length and caliber can be difficult at times, we sought to evaluate diagnostic utility of FPC to predict reconstructive surgery.
    Materials and methods: Reconstructive urology databases at Washington University and Columbia University were queried from 2010-2017. A total of 185 anterior urethroplasty patients met inclusion criteria. All surgeries were performed by a single surgeon. There were 102 patients that underwent preoperative FPC (7.5 Fr in… More >

  • Open Access

    ARTICLE

    Research on Maximum Return Evaluation of Human Resource Allocation Based on Multi-Objective Optimization

    Hong Zhu1,2,*

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 741-748, 2020, DOI:10.32604/iasc.2020.010108

    Abstract In this paper, a human resource allocation method based on the multi-objective hybrid genetic algorithm is proposed, which uses the multi-stage decision model to resolve the problem. A task decision is the result of an interaction under a set of conditions. There are some available decisions in each stage, and it is easy to calculate their immediate effects. In order to give a set of optimal solutions with limited submissions, a multi-objective hybrid genetic algorithm is proposed to solve the combinatorial optimization problems, i.e. using the multiobjective hybrid genetic algorithm to find feasible solutions at… More >

  • Open Access

    ARTICLE

    A Method for Decision Making Problems by Using Graph Representation of Soft Set Relations

    Nazan Çakmak Polat, Gözde Yaylali, Bekir Tanay

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 305-311, 2019, DOI:10.31209/2018.100000006

    Abstract Soft set theory, which was defined by D. Molodtsov, has a rich potential for applications in several fields of life. One of the successful application of the soft set theory is to construct new methods for Decision Making problems. In this study, we are introducing a method using graph representation of soft set relations to solve Decision Making problems. We have successfully applied this method to various examples. More >

Displaying 81-90 on page 9 of 100. Per Page