Search Results - (( emotional detection system algorithm ) OR ( whale optimization means algorithm ))

WHALE OPTIMIZATION NEURAL NETWORK FOR DAILY WATER LEVEL FORECASTING CONSIDERING THE CHANGING CLIMATE by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Teng, Yeow Haur

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Investigating dam reservoir operation optimization using metaheuristic algorithms by Lai V., Essam Y., Huang Y.F., Ahmed A.N., El-Shafie A.

Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Fai C.M., Afan H.A., Sapitang M., El-Shafie A.

“…For the test stage, the mean absolute error of the MLP�WA model decreased to 30% and from 31 to 38% as compared to the radial basis function�whale algorithm (RBF�WA) and GP models, respectively. …”

Real-time system for facial emotion detection using GPSO algorithm by Bashir, Mohammed Ghandi, R., Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

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Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”

Facial emotion detection using GPSO and Lucas-Kanade algorithms by Bashir, Mohammed Ghandi, Nagarajan, Ramachandran, Prof. Dr., Hazry, Desa, Prof. Madya Dr.

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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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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. …”
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Emotion detecting humanoid – the use of GPSO Algorithm by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

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Various Recognition approach in human faces by Karthigayan, M., Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Nagarajan, R., Puteh, Saad, Muhammed Firdaus, Hashim, Haniza, Yazid

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Human faces: a review from detection to recognition by Mohamed Rizon, Mohamed Juhari, Muthukaruppan, Karthigayan, Sazali, Yaacob, Ramachandran, Nagarajan, Puteh, Saad, P. L. EhKan

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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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A Simple Yet Reliable Facial Emotion Detection For Campus Environment by Amar Lokman, Mus’ab Sahrim, Wan Zakiah Wan Ismail, Sharma Rao Balakrishnan, Juliza Jamaludin

Facial emotion detection using Guided Particle Swarm Optimization (GPSO) by Bashir, Mohammed Ghandi, Nagarajan, R., Hazry, Desa

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Stress Level Detection using Fuzzy Logic / Nor Husna Nabila Khuzaini by Khuzaini, Nor Husna Nabila

“…This fuzzy logic system were successful develop. The result indicate in stress level detection based on fuzzy logic system that provide the symptom of stress and the facial emotion. …”
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Detecting emotions and depression through voice by Gunawan, Teddy Surya

“…A deep learning algorithm can detect emotion, including depression, using a voice signal. …”
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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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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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Multi-criteria optimization framework for cloudlet computing in WMANs: integrating VL-WIDE and AHP for enhanced decision-making by Muwafaq, Layth, Noordin, Nor K, Othman, Mohamed, Ismail, Alyani, Hashim, Fazirulhisyam

“…Our method employs a variable-length multi-objective whale optimization integrated with differential evolution (VL-WIDE) to tackle the optimization problem, dynamically adjusting to the WMAN environment while optimizing delay, energy consumption (both user device and cloudlet), and cloudlet deployment cost. …”
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Multiview face emotion recognition using geometrical and texture features by Goodarzi, Farhad

“…A 3D face pose estimation algorithm detects head rotations of Yaw, Roll and Pitch for emotion recognition. …”
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