Search Results - (( emotion detection method algorithm ) OR ( panel optimization swarm algorithm ))*

Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…In this study, MATLAB models of a DRL-based MPPT algorithm were developed, tested, and compared to simulation based on two established MPPT algorithms-the Particle Swarm Optimization (PSO), and the Perturb and Observe (P&O). …”

Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

“…The MPPT method applied to track maximum power from PV panel is particle swarm optimization (PSO). Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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PARTICLE SWARM OPTIMIZATION MAXIMUM POWER POINT TRACKING FOR PARTIALLY SHADED SOLAR PV by Alvin, Ngu Tien Leong

“…This study proposes a particle swarm optimization (PSO) algorithm based on MPPT for the PGS to operate under PSC. …”
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Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki by Mohd Zakki, Muhammad Iqbal

“…On the other hand, the implementation of conventional direct MPPT technique causes oscillation in MPP tracking due to the perturbative nature of the algorithms. Otherwise, the soft-computation MPPT methods by evolutionary algorithms such as Particle Swarm Optimization (PSO) algorithm require longer tracking time to prevent the false MPP tracking convergence. …”
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Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

“…Thus, this project aimed to study the emotion detection through EEG signal and proposed the right algorithm to process the signal. …”
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Comparative analysis of two-step GA-based PV array reconfiguration technique and other reconfiguration techniques by Muhammad Ajmal A., Ramachandaramurthy V.K., Naderipour A., Ekanayake J.B.

Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

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ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

“…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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GPSO versus GA in facial emotion detection by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system by Roslan M.F., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Zuhdi A.W.M.

Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection by Lai Po Hung, Suraya Alias

“…Perhaps the next task to catch on is emotion detection, the task of identifying emotions. …”
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NSGA-II and MOPSO Based Optimization for Sizing of Hybrid PV/ Wind / Battery Energy Storage System by Hlal, Mohamed Izdin, Ramachandaramurthya, Vigna K., Padmanaban, Sanjeevikumar, Kaboli, Hamid Reza, Pouryekta, Aref, Tuan Abdullah, Tuan Ab Rashid

“…The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. …”
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NSGA-II and MOPSO based optimization for sizing of hybrid PV / wind / battery energy storage system by Mohamad Izdin Hlal A., Ramachandaramurthya V.K., Sanjeevikumar Padmanaban B., Hamid Reza Kaboli C., Aref Pouryekta A., Tuan Ab Rashid Bin Tuan Abdullah D.

“…The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. …”

An intelligent maximum power point tracking algorithm for Photovoltaic System by Iman M.I., Roslan M.F., Ker P.J., Hannan M.A.

“…This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. …”

Detection of mental disorders based on the analysis of emotion, facial expressions and facial movements in a video stream by Nurzhanova, Aizhan, Mussabek, Miras, Ince, Gokhan, Mustaffa, Mas Rina, Zhumadillayeva, Ainur

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Design a photovoltaic system based on maximum power point tracking under partial shading by Ma’allin, Usama Abdullahi

“…The voltage and current of MSX60 PV module are subjected to various insolation conditions. The Particle Swarm Optimization (PSO) algorithm based MPPT has been implemented to track maximum power partial shading condition. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…Therefore, the proposed methods were effective in improving the process of automatic gender recognition from the emotional-based EEG signals.…”
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