Search Results - (( risk information method algorithm ) OR ( using optimization method algorithm ))
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm
Published 2025“…Realistic constraints are applied to formulate a multi-objective optimization problem. SPEA-II and traditional multi-objective optimization methods are used to solve this problem, resulting in a set of optimal portfolios. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…In model development, Ant-Miner was used which consists of three steps. In model validation, to quantify accuracy by approving the informational collection, Ant Colony Optimization Algorithm was used and it was compared with the J48 algorithm. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…Compared with established methods such as Ant Colony Optimization (ACO) and Genetic Algorithm (GA), MSCA exhibits superior computational efficiency while maintaining competitive accuracy. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management
Published 2009“…After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted Sum Method as well as the ε-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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Final Year Project -
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management
Published 2009“…After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted SumMethod as well as the e-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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An enhanced supplier selection model based on optimized analytic network process towards sustainable information technology outsourcing
Published 2022“…However, existing ITO supplier selection models lack of sustainability criteria and risk factors. Moreover, these methods rely on human judgment in weight allocation. …”
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Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer
Published 2024“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…It plays the role of objective function of the maintenance scheduling optimization problem. Using a production related heuristic method which is called system value method, the value of each workstation is determined. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…Experimental results show that the proposed algorithm works better than other two methods in terms of classifier accuracy with result of more than 99 percent successful segmentation of desired color in varying illumination. …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…This study will use the Extreme Learning Machine (ELM) method to classify the dengue by using the clinical data so that first aid can be given which can decrease some death risk. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Conference or Workshop Item -
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…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. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…A new optimization approach was proposed for redesign monitoring network wells using optimization algorithm based on the vulnerability of aquifer to contaminations, estimation error of sampling wells, nearest distance between wells, and source of contamination in the study area. …”
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