Social mimic optimization algorithm and engineering applications

Balochian, Saeed; Baloochian, Hossein

doi:10.1016/j.eswa.2019.05.035

Cited by 72 publications

(28 citation statements)

References 52 publications

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“…In other words, social imitation is the condition of adopting the behavior, conversation, or dressing of another person, which one sees as a guide. Based on this, an advanced is made towards a better understanding of human behavioral activities [34].…”

Section: Social Mimic Optimizationmentioning

confidence: 99%

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COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches

Toğaçar

Ergen

Cömert

2020

Computers in Biology and Medicine

492

360

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Coronavirus causes a wide variety of respiratory infections and it is an RNA-type virus that can infect both humans and animal species. It often causes pneumonia in humans. Artificial intelligence models have been helpful for successful analyses in the biomedical field. In this study, Coronavirus was detected using a deep learning model, which is a sub-branch of artificial intelligence. Our dataset consists of three classes namely: coronavirus, pneumonia, and normal X-ray imagery. In this study, the data classes were restructured using the Fuzzy Color technique as a preprocessing step and the images that were structured with the original images were stacked. In the next step, the stacked dataset was trained with deep learning models (MobileNetV2, SqueezeNet) and the feature sets obtained by the models were processed using the Social Mimic optimization method. Thereafter, efficient features were combined and classified using Support Vector Machines (SVM). The overall classification rate obtained with the proposed approach was 99.27%. With the proposed approach in this study, it is evident that the model can efficiently contribute to the detection of COVID-19 disease.

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Section: Social Mimic Optimizationmentioning

confidence: 99%

“…Eqs. (5)-(7) are used to implement the SMO algorithm [34]. For this study, the population size of 20 was selected, the maximum iteration parameter was selected as 10.…”

Section: Social Mimic Optimizationmentioning

confidence: 99%

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches

Toğaçar

Ergen

Cömert

2020

Computers in Biology and Medicine

492

360

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“…In addition, the chosen algorithms are simple in their execution with different inspiration fields. The implemented algorithms are the Rao optimization algorithm [33], SMO algorithm [34], and FRA [35]. The details of the proposed techniques are discussed next.…”

Section: Proposed Population-based Algorithmsmentioning

confidence: 99%

Photovoltaic Array Reconfiguration System for Maximizing the Harvested Power Using Population-Based Algorithms

2020

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Massive infiltration of photovoltaic (PV) systems into electric supply networks creates numerous challenges in the present era, as the PV systems become an alternative to non-renewable energy resources. Partial shading, nevertheless, is an essential problem which affects the productivity and life of PV plants. PV reconfiguration is known as a powerful technique to resolve this effect. It is achieved by rearranging the PV modules according to their temperature and levels of shade. Therefore, in this paper, we have utilized three simple population-based optimization algorithms that are known as the flow regime algorithm (FRA), the social mimic optimization algorithm (SMO), and the Rao optimization algorithm to dynamically restructure the PV array. The effectiveness of the proposed algorithms is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the results obtained are compared with a regular total-cross-tied (TCT) connection and recently published techniques such as the competence square (CS) and genetic algorithm (GA). Furthermore, to demonstrate the suitability of proposed approaches in real-time implementation, real-time irradiation data of a particular location are considered and fed into the proposed algorithms for effective shade dispersion. After successful shade dispersion, the total energy generated using the three proposed algorithms is calculated and compared with the TCT reconfigured system for one year. The presented energy calculations and revenue generation confirm that the power produced by the proposed FRA technique is 13% higher than that generated by the TCT configuration. Furthermore, the presented PV characteristics show a reduced number of multiple peaks in the system. Thus, the proposed FRA technique can be endorsed as a technique that is superior to other existing methods.

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“…Reference [21] presents an efficient and fast method for tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a PSO algorithm [22,23]. Also PSO algorithm is used to design a structure-specified mixed H2/H infinity controller for control balancing of Bicyrobo, which is an unstable system associated with many sources of uncertainties due to un-model dynamics, parameter variations, and external disturbances [24].…”

Section: Related Workmentioning

confidence: 99%

Adsorption control of a pipeline robot based on improved PSO algorithm

Wang

et al. 2020

Complex Intell. Syst.

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Particle swarm optimization (PSO) is a widely used method that can provide good parameters for the motion controller of mobile robots. In this paper, an improved PSO algorithm that optimize the control PID parameters of a specific robot have been proposed. This paper first presents a brief review of recently proposed PSO methods, and then presents a detailed analysis of the PID optimization algorithm, which uses H∞ theory to reduce the search space and fuses the information entropy to ensure the diversity of particles. Simulations in Matlab show that the algorithm can improve the convergence speed and get a better global optimization ability than the standard PSO algorithm. Experimental results present a sound effects for the control of the negative pressure adsorption motor in the power grid pipeline robot during its adsorption along the circular movements, which verifies the effectiveness of the proposed method.

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Social mimic optimization algorithm and engineering applications

Cited by 72 publications

References 52 publications

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches

COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches

Photovoltaic Array Reconfiguration System for Maximizing the Harvested Power Using Population-Based Algorithms

Adsorption control of a pipeline robot based on improved PSO algorithm

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