Allocation Method for Fuzzy Interval Graph Centers Based on Strong Connectivity

2017 ◽  
pp. 261-272
Author(s):  
Alexander Bozhenyuk ◽  
Margarita Knyazeva ◽  
Igor Rozenberg
Keyword(s):  
Interval Graph ◽  
Strong Connectivity ◽  
Allocation Method ◽  
Fuzzy Interval

A Control Allocation Method to Reduce Roll-Yaw coupling on Tailless Aircraft

2021 ◽  
Author(s):  
Thomas R. Shearwood ◽  
Mostafa R. Nabawy ◽  
William Crowther ◽  
Clyde Warsop
Keyword(s):  
Control Allocation ◽  
Allocation Method ◽  
Tailless Aircraft

Research on Regulation Compensation Allocation Method of Virtual Power Plant

2019 ◽  
Author(s):  
Jianlin Yang ◽  
Jingbang Li ◽  
Mingxing Guo ◽  
Yichao Huang ◽  
Aili Pang ◽  
...  
Keyword(s):  
Power Plant ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Allocation Method

scholarly journals Optimality Properties of the Disc Modulo Allocation Method for k-ary Multiple Key Hashing Files

1992 ◽  
Vol 35 (4) ◽  
pp. 390-394 ◽  
Author(s):  
C. C. Chang ◽  
H. F. Lin ◽  
C. Y. Chen
Keyword(s):  
Allocation Method ◽  
Optimality Properties

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

scholarly journals A New Method to Solve Fuzzy Interval Flexible Linear Programming Using a Multi-Objective Approach

2019 ◽  
Vol 11 (2) ◽  
pp. 221-238
Author(s):  
S. H. Nasseri ◽  
J. L. Verdegay ◽  
F. Mahmoudi
Keyword(s):  
Linear Programming ◽  
New Method ◽  
Multi Objective ◽  
Fuzzy Interval

An application of neutrosophic hypersoft mapping to diagnose brain tumor and propose appropriate treatment

2021 ◽  
pp. 1-23
Author(s):  
Muhmmad Saeed ◽  
Muhmmad Ahsan ◽  
Atiqe Ur Rahman ◽  
Muhammad Haris Saeed ◽  
Asad Mehmood
Keyword(s):  
Brain Tumor ◽  
Side Effects ◽  
Brain Tumors ◽  
Causes Of Death ◽  
Scientific Modeling ◽  
Inverse Mapping ◽  
Appropriate Treatment ◽  
Fuzzy Interval

Brain tumors are one of the leading causes of death around the globe. More than 10 million people fall prey to it every year. This paper aims to characterize the discussions related to the diagnosis of tumors with their related problems. After examining the side effects of tumors, it encases similar indications, and it is hard to distinguish the precise type of tumors with their seriousness. Since in practical assessment, the indeterminacy and falsity parts are frequently dismissed, and because of this issue, it is hard to notice the precision in the patient’s progress history and cannot foresee the period of treatment. The Neutrosophic Hypersoft set (NHS) and the NHS mapping with its inverse mapping has been design to overcome this issue since it can deal with the parametric values of such disease in more detail considering the sub-parametric values; and their order and arrangement. These ideas are capable and essential to analyze the issue properly by interfacing it with scientific modeling. This investigation builds up a connection between symptoms and medicines, which diminishes the difficulty of the narrative. A table depending on a fuzzy interval between [0, 1] for the sorts of tumors is constructed. The calculation depends on NHS mapping to adequately recognize the disease and choose the best medication for each patient’s relating sickness. Finally, the generalized NHS mapping is presented, which will encourage a specialist to extricate the patient’s progress history and to foresee the time of treatment till the infection is relieved.

Sign in / Sign up

Export Citation Format

Share Document