Search Results - (( parameter evaluation methods algorithm ) OR ( parameter optimisation based algorithm ))

Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

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Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

“…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

“…The best algorithm for each parameter was selected based on these criteria. …”
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PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

“…The important point is to evaluate the range of PID parameter which used in the GAs programmed to find the best value of this parameter. …”
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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. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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Analysis of the ECG signal using SVD-based parametric modelling technique by Baali, Hamza, Salami, Momoh Jimoh Emiyoka, Akmeliawati, Rini, Aibinu, Abiodun Musa

“…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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Modelling and calibration of high-pressure direct injection compressed natural gas engine by Mohd Fadzil, Abdul Rahim

“…The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. Based on stated methodologies, the following findings were recorded; the analytical model of the HPDI-CNG vehicle predicted a maximum of 123.11 Nm of brake torque at 60 bar of injection pressure. …”
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Impact of low-dose protocols on computed tomography of lung cancer screening on the intrinsic performance metrics: a phantom study by Karim, M.K.A., Khalidi, M. E., Chew, M. T., Kechik, M. M. A., Mazlan, D., Ng, K. H.

“…Introduction: This research aims to assess the task-based performance of low dose CT lung examination with different acquisition parameters, evaluate the acquisition parameters of lung cancer in low dose CT lung examination, and explore the effect of the iterative reconstruction (IR) algorithm on the image quality of low dose CT for CT lung examination. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

“…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

“…At this stage, two popular SVM selection parameter methods, trial and error and cross validation were investigated and compared. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

“…Optimisation is difficult to optimise as there are three parameters that need to be tuned, Kp, Integral parameter, Ki, and derivative parameter, Kd. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment by Abdul Manap, Redzuan, Ling, Shao, Frangi, Alejandro Federico

“…However, this approach requires an intensive training phase to optimise the regression parameters. In this paper, we overcome this limitation by proposing an alternative BIQA model that predicts image quality using nearest neighbour methods which have virtually zero training cost. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

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