A Developed Artificial Bee Colony Algorithm Based on Cloud Model

Jin, Ya‐Qiu; Sun, Yu; Ma, Hongwei

doi:10.3390/math6040061

Cited by 13 publications

(8 citation statements)

References 38 publications

(48 reference statements)

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“…The cloud generator is the key algorithm [35][36][37] for converting qualitative and quantitative cloud models and is the basis for uncertainty inference rule building. The cloud drop generation process is shown in Figures 3 and 4 Forward cloud generator is the uncertainty conversion algorithm from qualitative to quantitative representations.…”

Section: Cloud Generatormentioning

confidence: 99%

Research on Dynamic Assessment Method of Earthquake Scene Rescue Performance Based on AHP and Cloud Model

et al. 2022

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In view of the ambiguity and randomness of the assessment of earthquake scene rescue performance, this paper proposes an integrated assessment method considering quantitative and qualitative influencing factors from three levels: search, rescue and medical treatment. Firstly, this study constructs an assessment index system of rescue performance at the earthquake scene based on the International Search and Rescue Advisory Group (INSARAG) guidelines set by International Search and Response. Secondly, the subjective weights and objective weights of each index were calculated using the hierarchical analysis process (AHP) and cloud model, respectively. The comprehensive weights were calculated using weighted analysis, and the performance assessment results were visually expressed by cloud model images. Finally, the study was applied to an earthquake rescue case with an initial assessment of 4.0065, and its performance was improved by 4.36% when the rescue process was optimized. The assessment results show that earthquake rescue performance can be estimated, and the rationality and effectiveness of the method was validated.

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Section: Cloud Generatormentioning

confidence: 99%

Research on Dynamic Assessment Method of Earthquake Scene Rescue Performance Based on AHP and Cloud Model

et al. 2022

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“…Using the multi-objective technique, the fitness result was calculated to confirm the problem. Experimental results [39] revealed the efficiency of the provided algorithm Artificial bee colony (ABC), a meta-heuristic search algorithm inspired by the intelligent foraging behaviour of honey bees in nature. With fewer sensor nodes, a hybrid approach [22] employs the descent method and the parallel strengthening algorithm to tackle both the area coverage and barrier coverage problems.…”

Section: B) Related Projectsmentioning

confidence: 99%

To Prolong the life of IoT in the fifth generation utilising a parallelly implemented Multiobjective Algorithm with Mapping Reduce

Qamar

2022

Preprint

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Extended dimensions, high speeds, superior reliability, and negligible latency, increased capacity, and better QoS are some of the major objectives or challenges that must be communicated in the near future, i.e., far away 4G. To address these issues, urgent advancements in cellular network architecture are required [7]. The introduction of the fifth generation in 2020 will have an impact on a wide range of technological fields. Smaller delays, faster data transmission, and better connectivity will all be features of 5th generation. The Internet of Things will undergo significant changes. The internet of things (IoT) is a developing technology of internet-connected physical devices with the ability to collect and share large amounts of data. High speeds, maximum connectivity, ultralow latency, and universal coverage will all be available with 5th generation technology. The coverage problem in wireless sensor networks (WSNs) is interpreted by calculating the efficacy of how a web zone is observed with its sensor networks.To address these coverage issues, comprehensive coverage protocols have been devised [6]. Organizations are expected to begin establishing the number of these connected devices after considering all parameters such as increasing transmitted data speed and resolving latency issues.To solve the coverage problem and to extend the lifespan of the Internet of Things they used the parallel genetic algorithm with a huge number of connections. The algorithm should consider both node redundancy and coverage while evaluating the result of the current configuration of effective nodes.

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“…The fitness outcome was derived to confirm the problem by using the multi-objective approach. The effectiveness of the presented algorithm artificial bee colony (ABC) is a meta-heuristic search algorithm inspired by the intelligent foraging behavior of honey bees in nature was described by their experimental results [37].…”

Section: B) Related Workmentioning

confidence: 99%

Ensured Lifespan of IoT in 5G Depends on Metaheuristic Algorithm-Genetic Algorithm

Qamar

2022

Preprint

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Mobile Cellular networks are developing to the period of 5G, for empowering elegant and inventive resources of IoT, the new 5 th generation radio (NR), lifelong evolution like (LTE-A) high tech are intended. Although, the current LTE-A master entente namely group paging technique is still steadily influenced concerning person-to-person communication following the varying characteristics of an extensive variety of Internet of things devices. From way back, utmost Internet of Things are operated with the help of battery which the rate of power consumption is the deciding factor of their battery lifetime, therefore energy-efficient transferring protocols of data are of outstanding importance future generation Internet of Things networks. One of the examples in improving the energy efficiency of Internet of things networks is group paging. Yet, the approach of grouping for the Internet of things mechanism is quite not much an important topic to discuss. Hence, this paper suggested an inventive different criterion transmutative optimization, specifically, genetic algorithm. The output attained from simulation confirms that our suggested technique can appreciably improve the energy efficiency of Internet of things gadgets. The results of the simulation of this suggested algorithm illustrate that it will intersect at the classic solution fast and convince the demand of small node implementation rate and a high rate of coverage, thus extending the lifespan of the network accurately.

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A Developed Artificial Bee Colony Algorithm Based on Cloud Model

Cited by 13 publications

References 38 publications

Research on Dynamic Assessment Method of Earthquake Scene Rescue Performance Based on AHP and Cloud Model

Research on Dynamic Assessment Method of Earthquake Scene Rescue Performance Based on AHP and Cloud Model

To Prolong the life of IoT in the fifth generation utilising a parallelly implemented Multiobjective Algorithm with Mapping Reduce

Ensured Lifespan of IoT in 5G Depends on Metaheuristic Algorithm-Genetic Algorithm

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