Search Results - (( problem segmentation learning algorithm ) OR ( parameter optimisation based algorithm ))

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
Get full text
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
Get full text
Get full text
Get full text

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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

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. …”
Get full text
Get full text

A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

Get full text
Get full text
Get full text

Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…These algorithms have been applied to the problem of image segmentation. …”
Get full text
Get full text

Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

“…In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. …”
Get full text
Get full text

Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. …”
Get full text
Get full text

Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

“…In comparison, the proposed ssSKF algorithm supersedes the original population-based Simulated Kalman Filter (SKF) algorithm by operating with only a single agent, and having less parameters to be tuned. …”
Get full text
Get full text

Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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.

Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
Get full text
Get full text

Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
Get full text
Get full text

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
Get full text
Get full text

An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

“…In line with the upcoming of a new field called search-based software engineering (SBSE), many newly developed t-way strategies adopting meta-heuristic algorithms can be seen in the literature for constructing interaction test suite (such as simulated annealing (SA), genetic algorithm (GA), ant colony optimisation algorithm (ACO), particle swarm optimisation (PSO), harmony search (HS) and cuckoo search (CS). …”
Get full text
Get full text
Get full text

Automated visual defect detection using deep learning by Loh, Xiao

“…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
Get full text
Get full text

Old Jawi manuscript: Digital recognition / Zaidi Razak by Zaidi, Razak

“…The literature review in this research looks at works conducted in the past on line and character segmentation as well as recognition systems. The information gathered is useful for the development of a line segmentation algorithm, a new character segmentation algorithm, as well as a recognition algorithm which is based on the use of a unique code and Hamming distance calculation. …”
Get full text
Get full text