Search Results - (( wave optimisation based algorithm ) OR ( waste selection method algorithm ))
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1
RFID data reliability optimiser based on two dimensions bloom filter
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2
A smart handover strategy for 5G mmWave dual connectivity networks
Published 2023“…The developed algorithm underwent testing using a 5G mmWave statistical channel model that emulates a dynamic channel matrix, including fading and the Doppler effect. …”
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3
Active intelligent control of vibration of flexible plate structures
Published 2011“…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
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4
Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
5
A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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6
Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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7
Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
8
Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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9
Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
Published 2017“…The model output optimisation by genetic algorithm (GA) produces higher biogas production compared to the optimisation using statistical methods. …”
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10
Incorporation of High Recyclability Material Selection in Computer Aided Design
Published 2014“…In this paper, the use of fuzzy inference system and genetic algorithm is proposed to optimize the multi-objective problem in the selection of recyclable materials. …”
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11
A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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12
Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm
Published 2018“…Primarily, this research is about the optimization of triaxial ceramic employing the POFA process by the Taguchi design and Flower Pollination Algorithm (FPA). The recycled POFA was evaluated through the POFA layer formation method where selected POFA layers were employed as filler raw material. …”
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13
Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
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14
Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review
Published 2023Conference Paper -
15
Planar array failed element(S) radiation pattern correction: A comparison
Published 2023“…This paper compares the few available optimization methods, namely, simulated annealing (SA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Pattern Search (PS) methods. …”
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16
Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam
Published 2023“…The Malaysian Ageing and Retirement Survey (MARS) Data Wave 1 is used for this study where the data was sampled via multiple-stage sampling framework where each region is stratified by urban and rural areas called enumeration blocks (EBs) which are proportionate to the population size of each region across 3,384 households. …”
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17
Glammix / Mehmet Zaidell Kamarudzaman … [et al.]
Published 2024“…Glammix utilizes AI algorithms to analyze user preferences, clothing styles, and fit. …”
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18
Modelling of CO2 Laser Materials Processing by Networked Neuro-Dimension Fuzzy Intelligent System
Published 2013“…It was concluded that the setting of proper network algorithm and rules, can actually help the industry to perform laser machining better by saving huge waste materials by employing the approach presented in this paper as compared to the traditional trial-and-error method.…”
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19
Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)...
Published 2019“…The model training flow will have 2 classifier groupings which are control group and auto machine learning (ML) where feature selection with redundancy elimination method to be applied on input data to reduce the number of variables to minimum prior modeling flow. …”
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20
Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…Thus, the never selected actions can present a higher reward when compared to already executed actions. …”
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