Search Results - (( _ evaluation model algorithm ) OR ( parameters variation based algorithm ))

Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems by Mok, Ren Hao, Mohd Ashraf, Ahmad

“…This paper explores the tuning of the Sigmoid Proportional-Integral-Derivative (SPID) controller using variations of the Smoothed Functional Algorithm (SFA) for the underactuated Multiple-Input Multiple-Output (MIMO) twin-rotor system. …”
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Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

“…Specifically, ESMA was evaluated on the parameter estimation in several photovoltaic models, i.e., the one-diode model (ODM), dual-diode model (DDM), and PV-module model (PMM). …”
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A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

“…This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…After optimizing the proposed fuzzy model by means ofgenetic algorithm, the resulted planner produces shorter paths in shorter runtimes with limited variations in results of different runs of the planner. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

“…To address these challenges, the proposed thesis introduces a novel model-based hybrid variational level-set method, termed VKMHLS, specifically tailored for object detection in grayscale images. …”
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Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations by Amalin Aisya binti Mohd Awi

Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…However, most of the existing evolutionary algorithms have some adjustable parameters which depend on subjective experience or prior knowledge. …”
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Design of QFT-based self-tuning deadbeat controller by Mansor, Hasmah, Mohd Noor, Samsul Bahari

“…By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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Design of QFT-based self-tuning deadbeat controller by Mansor, Hasmah, Mohd Noor, Samsul Bahari

“…By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. …”
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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.

“…The objectives were: (1) to prepare robust hybrid ANN models; (2) to study the combination of ANN models and optimization algorithms; and (3) to study uncertainty related to the input parameters of the models, whereby three scenarios with different inputs were considered. …”

Adaptive linux-based TCP congestion control algorithm for high-speed networks by Alrshah, Mohamed A.

“…Further, we propose a novel mathematical model to calculate the average throughput of the AF-based CCA. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…The main features of the proposed controller are; quick recovery of motor’s speed from load disturbances and insensitivity to parameter variation over a wide speed range. The proposed controller is a hybrid model reference adaptive speed controller (HMRASC) which mainly consists of two functional blocks. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…In addition, the solutions have been evaluated based on pre-defined performance metrics and the outcomes of the optimization framework were compared with the other existing optimization techniques to evaluate the potency and the productivity of the developed MLPSO algorithm. …”

Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
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Optimization and Decomposition Methods in Network Traffic Prediction Model: A Review and Discussion by Jinmei Shi, Yu-Beng Leau, Kun Li, Yong, Jin Park, Zhiwei Yan

“…This article discusses past network traffic prediction research and critically examines the optimization and decomposition technologies used in the model, lists the model parameter structure based on the research methodology, the data set used, the evaluation criteria and so on. …”
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

“…A multilayer feed-forward network with a back propagation algorithm is applied to estimate the TEC over Parit Raja (Lat. 1�52?…”