Parameter tuning of software effort estimation models using antlion optimization

Alabajee, Marrwa Abd-AlKareem; Al-Saati, Najla Akram; Alreffaee, Taghreed Riyadh

doi:10.12928/telkomnika.v19i3.16907

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…Two decision tree classification methods were introduced in [24] for automatically find priority rules to solve the resource constrained project scheduling problem (RCPSP). A [25], [26] centralized 3dimensional radio resources (namely, time, frequency, and power) allocation and scheduling approach for control-plane and [27] user-plane (C-/U-plane) separation architectures for fifth generation mobile networks.…”

Section: Methodsmentioning

confidence: 99%

Elastic net feature selected multivariate discriminant mapreduce classification

Nakkiran

Thulasiraman²

2022

IJEECS

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Analyzing the <span>big stream data and other valuable information is a significant task. Several conventional methods are designed to analyze the big stream data. But the scheduling accuracy and time complexity is a significant issue. To resolve, an elastic-net kernelized multivariate discriminant map reduce classification (EKMDMC) is introduced with the novelty of elastic-net regularization-based feature selection and kernelized multivariate fisher Discriminant MapReduce classifier. Initially, the EKMDMC technique executes the feature selection to improve the prediction accuracy using the Elastic-Net regularization method. Elastic-Net regularization method selects relevant features such as central processing unit (CPU) time, memory and bandwidth, energy based on regression function. After selecting relevant features, kernelized multivariate fisher discriminant mapr classifier is used to schedule the tasks to optimize the processing unit. Kernel function is used to find higher similarity of stream data tasks and mean of available classes. Experimental evaluation of proposed EKMDMC technique provides better performance in terms of resource aware predictive scheduling efficiency, false positive rate, scheduling time and memory consumption.</span>

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Section: Methodsmentioning

confidence: 99%

Elastic net feature selected multivariate discriminant mapreduce classification

Nakkiran

Thulasiraman²

2022

IJEECS

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“…The designed technique failed to consider reliability estimation. Ant colony optimization (ACO) [4], antlion optimization (ALO) algorithm [5] were discussed. Differential search algorithm (DSA) was developed in [6] for optimal choice and allocation of shunt Flexible AC transmission systems (FACTS) device.…”

Section: Related Workmentioning

confidence: 99%

“…By applying the generative latent Dirichlet allocation model, the probability of the failure occurrences of the components is measured using optimal test cases. Therefore, the probability distribution [29] is obtained as (5).…”

Section: Generative Likelihood Latent Dirichlet Allocation Modelmentioning

confidence: 99%

Multicriteria Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression for software quality management

Chennappan

Thulasiraman²

2021

IJEECS

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The paper presents the software quality management is a highly significant one to ensure the quality and to review the reliability of software products. To improve the software quality by predicting software failures and enhancing the scalability, in this paper, we present a novel reinforced Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression (RCSOLDA-RIR) technique. At first, Multicriteria reinforced Cuckoo search optimization is used to perform the test case selection and find the most optimal solution while considering the multiple criteria and selecting the optimal test cases for testing the software quality. Next, the generative latent Dirichlet allocation model is applied to predict the software failure density with selected optimal test cases with minimum time. Finally, the Ruzchika indexive regression is applied for measuring the similarity between the preceding versions and the new version of software products. Based on the similarity estimation, the software failure density of the new version is also predicted. With this, software error prediction is made in a significant manner, therefore, improving the reliability of software code and service provisioning time between software versions in software systems is also minimized. An experimental assessment of the RCSOLDA-RIR technique achieves better reliability and scalability than the existing methods.

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“…In demand forecasting, FA-based gated recurrent unit model outperforms standard gated recurrent unit (GRU) and long short-term memory models (LSTM) in accuracy, especially for a concrete block manufacturing company in Iraq [29]. The antlion optimization (ALO) algorithm proves highly efficient for estimating parameters in modified constructive cost models (COCOMO), surpassing other algorithms in various scenarios and datasets [30]. For text clustering, the medoid grey wolf optimization (M-GWO) algorithm excels at handling outlier and noise data, showing superior performance compared to genetic, firefly, GWO, and k-means algorithms in achieving high-quality document clustering [31].…”

Section: Introductionmentioning

confidence: 99%

Firefly algorithm tuning of PID position control of DC motor using parameter estimator toolbox

Jallad,

Badran

2024

Bulletin EEI

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This paper aims to design an accurate angular position control for DC motors using a proportional integral derivative (PID) controller. The estimated DC motor parameters have been calculated using the parameter estimator toolbox in MATLAB, Arduino Mega 2560 and speed sensor to build an accurate model in MATLAB. The optimized PID coefficients are found for the DC motor model using the firefly algorithm (FA), which aims to make the actual angle match the desired value without overshooting and oscillations. The PIC16F877A microcontroller was used to implement the code based on optimized PID coefficients found in MATLAB/Simulink to generate the suitable pulse width modulation (PWM) output. In this work, step input was tested to analyze the characteristics of the system response in terms of rise time, settling time and overshoot. It was found that the controller output response curve which is produced from FA-based-PID reached the desired position without overshoot and any oscillations. The findings established that closed-loop control of any system using a system identification toolbox and optimized PID technique can be applied in real applications using low-cost controllers and sensors such as PIC16F877A microcontroller and analog rotary position sensor, respectively.

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Parameter tuning of software effort estimation models using antlion optimization

Cited by 4 publications

References 14 publications

Elastic net feature selected multivariate discriminant mapreduce classification

Elastic net feature selected multivariate discriminant mapreduce classification

Multicriteria Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression for software quality management

Firefly algorithm tuning of PID position control of DC motor using parameter estimator toolbox

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