Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex

Chen, Liang; Huang, Huan; Tang, Panyu; Yang, Dong; Yang, Haonan; Ghadimi, Noradin

doi:10.1080/15567036.2022.2074174

Cited by 91 publications

(27 citation statements)

References 43 publications

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“…The most desirable search agent in every sets is given by accessing the cost function. In this article, 45% of the population has been gained by the OBL algorithm 36 . As well as the chaos theory are utilized here for providing a better convergence and exploration.…”

Section: Methodsmentioning

confidence: 99%

“…In this article, 45% of the population has been gained by the OBL algorithm. 36 As well as the chaos theory are utilized here for providing a better convergence and exploration. According to this theory, we have produced pseudo-accidental parameters as an alternative to accidental ones that improve the algorithm convergence speed.…”

Section: Advanced Sea Lion Optimization Algorithmmentioning

confidence: 99%

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Predicting building energy utilization with energy plus simulation and advanced sea lion optimization algorithm based on Elman neural network

Al-Fadheeli

Bouteraa

Mohammed

et al. 2023

Concurrency and Computation

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There are different methods for modeling a structure and the building with the heat from the exterior and interior sources for evaluating a good performance, predicting energy utilization. Various methods, differing from simple regression to techniques, which are according to the physical ideology, could be utilized in simulation. There is a prevalent explanation for whole these methods, in which the input parameters are according to an actual database when they are accessible, or else, the energy utilization assessment would be underestimated or over-estimated. In this investigation, two procedures have been presented that one is according to Elman neural network based on advanced sea lion optimization algorithm and the other one is according to physical ideology, that is, energy plus, which is prediction equipment for predicting building energy utilization. It can be seen that both methods can be proper for energy utilization prediction. In addition, an analysis that is parametric is implemented for the reflected structure on energy plus for evaluating the impact of some variables like the occupation of the building profile and weather database on predicting.

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Section: Methodsmentioning

confidence: 99%

Section: Advanced Sea Lion Optimization Algorithmmentioning

confidence: 99%

Predicting building energy utilization with energy plus simulation and advanced sea lion optimization algorithm based on Elman neural network

Al-Fadheeli

Bouteraa

Mohammed

et al. 2023

Concurrency and Computation

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show abstract

“…In addition, the concentration voltage drops are attained as follows [38]:

\begin{eqnarray} {V_{conc}} = \frac{{R \times T}}{{4 \times F}} \times \left[ {\ln \left( {\frac{{P_{{{\rm{H}}_2}}^2 \times {P_{{{\rm{O}}_2}}}}}{{P_{{{\rm{H}}_2}{\rm{O}}}^2}}} \right) - \ln \left( {\frac{{P_{{{\rm{H}}_2}}^{*2} \times P_{{{\rm{O}}_2}}^*}}{{P_{{{\rm{H}}_2}{\rm{O}}}^{*2}}}} \right)} \right]\nonumber\\ \end{eqnarray}

…”

Section: System Modellingmentioning

confidence: 99%

A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

Ren,

Hou,

Jia

et al. 2023

IET Renewable Power Gen

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This study provides an optimal and efficient energy management strategy (EMS) for the cost-effective performance of a combined solar and green energy microgrid in both independent and grid-connected modes. A microgrid is formed by the system that includes a fuel cell (FC), a battery storage (BS), and a photovoltaic system (PV). Evidently, the unguaranteed features of the renewable energy and load electricity generate instability problems as well as economic ones, like operational expenses. To tackle these issues, a novel procedure is proposed that has been improved by a modified metaheuristic algorithm, called chaotic map-based chameleon Swarm Algorithm (CCSA). In this method, the simulation is based on a one-day planning perspective. The method aims to supply the power requirements of the load at the lowest possible cost under a constant DC bus voltage, protect the battery from overcharging and depletion, and improve the efficiency of the total system. To illustrate the suggested method's effectiveness, the simulation results of CCSA are compared with some studied methods in the literature, including GAMS, bald eagle search optimization algorithm (BEOA), original chameleon swarm algorithm (CSA), and grey wolf optimization algorithm (GWOA).

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“…In addition to image processing applications, these heuristic optimization techniques are effective in various fields. Chen et al 16 enhanced the overall design of a sports complex's heating, cooling, and electricity system with the African vulture optimization approach. In this manner, they reduce energy consumption, minimizing costs and environmental impact.…”

Section: Introductionmentioning

confidence: 99%

Ensemble the recent architectures of deep convolutional networks for skin diseases diagnosis

Duman

Tolan

2023

Int J Imaging Syst Tech

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If you decided to utilize deep learning in any image processing application, you would be faced with the issue, "Which architecture should I use?" due to the proliferation of existing CNN models and their advancements. Unfortunately, your answer will only be partially correct because each alternative has its advantage. The underlying idea of this research is to combine recent CNN models instead of selecting just one for optimal accuracy. Our study applied this idea to color lesion images to diagnose skin diseases. By ensembling, the recent CNNs, over 99% classification accuracy and over 97% sensitivity were achieved for the ISIC-2017 dataset, which contains 2000 lesion images. Our mean sensitivity and AUC values for classifying 10000 color lesion images into seven different skin diseases (ISIC-2018) were 0.825% and 0.922%, respectively.In categorizing over 25000 images from the ISIC 2019 dataset, our suggested technique achieved a mean sensitivity of over 90%.

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Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex

Cited by 91 publications

References 43 publications

Predicting building energy utilization with energy plus simulation and advanced sea lion optimization algorithm based on Elman neural network

Predicting building energy utilization with energy plus simulation and advanced sea lion optimization algorithm based on Elman neural network

A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

Ensemble the recent architectures of deep convolutional networks for skin diseases diagnosis

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