Search Results - (( model validation swarm algorithm ) OR ( image classification based algorithm ))

Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
Get full text
Get full text
Get full text

Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
Get full text
Get full text
Get full text

OPTIMIZATION OF PID CONTROLLER PARAMETERS USING ARTIFICIAL FISH SWARM ALGORITHM by SOOMRO, WAFA ALI SOOMRO

“…The Literature Review chapter thoroughly describes the Idea of Swarm Intelligence and Swarm Optimization. In methodology, the mathematical model of the algorithm is briefly described. …”
Get full text
Get full text

An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
Get full text
Get full text
Get full text

Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization by Ab Rashid, Mohd Fadzil Faisae, Nik Mohamed, Nik Mohd Zuki, Romlay, Fadhlur Rahman Mohd, Razali, Akhtar Razul, Asmizam, Mokhtar

“…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
Get full text
Get full text

Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

“…Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
Get full text
Get full text

Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

“…This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
Get full text
Get full text

Fractional chaotic ensemble particle swarm optimizer for identifying the single, double, and three diode photovoltaic models� parameters by Yousri D., Thanikanti S.B., Allam D., Ramachandaramurthy V.K., Eteiba M.B.

Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
Get full text
Get full text
Get full text

A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

Intelligent Prediction System for Gas Metering System using Particle Swarm Optimization in Training Neural Network by Rosli, N.S., Ibrahim, R., Ismail, I.

“…The intelligent prediction system has been developed for gas measurement validation. Then the project focused on the application of particle swarm optimization (PSO) and Genetic Algorithm (GA) in training neural network prediction model in enhancing the performance of Intelligent Prediction System (IPS). …”
Get full text
Get full text

Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. The validation results proved the effectiveness of both the proposed methods, which identified the kinetics and minimized the model response errors perfectly.…”
Get full text
Get full text
Get full text

An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

Get full text
Get full text

Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
Get full text
Get full text

Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm by Hannan M.A., Akhtar M., Begum R.A., Basri H., Hussain A., Scavino E.

“…Costs; Efficiency; Routing algorithms; Scheduling; Solid wastes; Vehicle routing; Capacitated vehicle routing problem; Modified particle swarm optimization; Optimized models; Route optimization; Solid waste collection; Threshold waste level; Travel distance; Waste collection; Particle swarm optimization (PSO); fuel; algorithm; numerical model; optimization; routing; solid waste; transport vehicle; waste disposal; algorithm; Article; capacitated vehicle routing problem model; controlled study; cost; decision making; environmental impact; motor vehicle; nonbiological model; particle swarm optimization algorithm; priority journal; problem solving; process optimization; socioeconomics; solid waste management; travel; validation process; economics; solid waste; waste management; Algorithms; Costs and Cost Analysis; Solid Waste; Waste Management…”

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. …”
Get full text
Get full text
Get full text

ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS by Toha, Siti Fauziah, Tokhi, M. O.

“…An adaptive neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm is developed in search for non-parametric model for the TRMS. …”
Get full text
Get full text
Get full text

Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin by Che Wan Samsudin, Che Wan Sufia

“…Both simulated and real-world experiments are used as a basis to rigorously test and validate the predictive capability of the model. The results of the study demonstrate the effectiveness of the proposed model. …”
Get full text
Get full text

A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
Get full text
Get full text

Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model by Azrag, Mohammed Adam Kunna, Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. The validation results proved the effectiveness of both the proposed methods, which identified the kinetics and minimized the model response errors perfectly.…”
Get full text
Get full text
Get full text