Search Results - (( variable generation based algorithm ) OR ( variable machine learning algorithm ))

Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…Therefore for that reason we develop another algorithm for clustering space which contributes a higher accuracy compares to K-means cluster with less subclass number, higher stability and bounded time of classification with respect to the variable data size. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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Developing an ensembled machine learning prediction model for marine fish and aquaculture production by Rahman L.F., Marufuzzaman M., Alam L., Bari M.A., Sumaila U.R., Sidek L.M.

“…Global changes in climatic variables have impacted and continue to impact marine fish and aquaculture production, where machine learning (ML) methods are yet to be extensively used to study aquatic systems in Malaysia. …”

Ensemble learning for multidimensional poverty classification by Azuraliza Abu Bakar, Rusnita Hamdan, Nor Samsiah Sani

“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine by Molla Salilew, W., Ambri Abdul Karim, Z., Alemu Lemma, T.

“…The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas turbine fault detection and isolation task. …”
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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine by Molla Salilew, W., Ambri Abdul Karim, Z., Alemu Lemma, T.

“…The present study investigates the accuracy of different machine learning classification algorithms with three different data smoothing techniques for gas turbine fault detection and isolation task. …”
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Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

“…In this thesis, the human handwritten signature is introduced as a novel cover media (c) in conjunction with a steganography algorithm since there is a level of variability (i.e intra-user variability) within handwritten signature samples of an individual. …”
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Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS by Zhang, Guanjin, Roslan, Siti Nur Aliaa, Mohd Shafri, Helmi Zulhaidi, Zhao, Yanxi, Wang, Ci, Quan, Ling

“…The model combining LSTM algorithm and NIRv had the best prediction effect and relatively stable performance in single year. …”
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION by Sivarao, Subramonian

“…The aim of this scientific research is to design knowledge based linguistic rules, algorithm, architecture & learning ability and further develop fuzzy model for laser machining kerf edge quality prediction. …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

“…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. An adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order for the mobile robot to learn. …”
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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management by Ali, R.A., Nik Ibrahim, N.N.L., Ghani, W.A.W.A.K., Sani, N.S., Lam, H.L.

“…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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