Search Results - intelligence valid ((means algorithm) OR (_ algorithm))

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

“…The experimental data is then validated using metrics such as coefficient of determination (R2), root mean square error, and root mean error. …”

DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS by FIRAS BASIM, ISMAIL ALNAIMI

“…The encoding and optimization process using genetic algorithms has been applied successfully. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. …”
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

“…This thesis presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm - Least Square Support Vector Machine (CS-LSSVM). …”
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Students’ perceptions towards the ethical considerations of using artificial intelligence algorithms in clinical decision-making by Lin, Galvin Sim Siang, Tan, Wen Wu, Hashim, Hasnah

“…Abstract Aim: The present study aimed to explore the perceptions of dental students regarding the ethical considerations associated with the use of artificial intelligence (AI) algorithms in clinical decision-making. …”
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Hub Angle Control for A Single Link Flexible Manipulator Based on Cuckoo Search Algorithm by aiman Azrael, Shaiful Nahar Sukri, Siti Sarah Zahidah, Nazri, Muhamad Sukri, Hadi, Annisa, Jamali, Hanim, Mohd Yatim, Intan Zaurah, Mat Darus

“…Then, the performance of proposed algorithms was validated based on three robustness methods known as mean squared error, pole zero diagram stability and correlation tests. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

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Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization by Khamis, Alias

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Mayfly Algorithm for Modelling a Horizontal Flexible Plate Structure by Aida Nur Syafiqah, Shaari, Muhamad Sukri, Hadi, Annisa, Jamali, Intan Zaurah, Mat Darus

“…Researchers have devised various approaches to suppress unwanted vibrations, with contemporary studies often employing system identification techniques utilizing swarm intelligence algorithms to construct dynamic models of flexible structures. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler High Temperature Superheater Trip using Artificial Intelligence Monitoring System by Alnaimi, F. B. I., Al-Kayiem, Hussain H.

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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

“…Commonly, the Fuzzy rules are optimized using offline optimization methods such as Differential Evolutionary (DE), Particle Swarms Optimization (PSO), or Artificial Neural Network (ANN) algorithms. In this research, Differential Evolution (DE) algorithm is modified to enhance the Fuzzy logic output gains to increase the performance of PID portion of the Fuzzy-PID controller. …”
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Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model by Alade, Ibrahim Olanrewaju, Bagudu, Aliyu, Oyehan, Tajudeen A., Abd Rahman, Mohd Amiruddin, Saleh, Tawfik A., Olatunjif, Sunday Olusanya

“…In this work, we proposed a very rapid and accurate computational intelligent approach using Genetic Algorithm/Support Vector Regression models to estimate the real part of the refractive index for oxygenated and deoxygenated hemoglobin samples. …”
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Metaheuristic research: a comprehensive survey by Hussain, Kashif, Mohd Salleh, Mohd Najib, Shi, Cheng, Yuhui, Shi

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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.] by M. A., Hambali, Y. K, Saheed, M. D, Gbolagade, M, Gaddafi

“…In doing this, two ANN algorithms (MLP and RBF) and SMO algorithm were employed and compared. …”
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ANFIS Identification Model of an Advanced Process Control (APC) Pilot Plant by Baloch, M A, Ismail, Idris, Hanif, NHHM, Baloch , Taj Mohamad

“…The developed model has been validated using the best fit criteria against the measured data of the pilot plant. …”
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A Novel Model on Curve Fitting and Particle Swarm Optimization for Vertical Handover in Heterogeneous Wireless Networks by Goudarzi, S., Hassan, W.H., Anisi, M.H., Soleymani, S.A., Shabanzadeh, P.

“…This study uses two modules that utilize the particle swarm optimization (PSO) algorithm to predict and make an intelligent vertical handover decision. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

“…This study investigates the use of a novel Proposed Self-Calibration Algorithm (PSCA) of multi pressure sensors in real time on robotic hand glove system. …”
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Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions by Ehteram M., Ghotbi S., Kisi O., Ahmed A.N., Hayder G., Fai C.M., Krishnan M., Afan H.A., EL-Shafie A.