Search Results - (( variable learning based algorithm ) OR ( variable mobile learning algorithm ))

IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

“…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. …”
Get full text
Get full text

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

A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot by Samsudin, Khairulmizam, Ahmad, Faisul Arif, Mashohor, Syamsiah

“…In order to achieve high accuracy, a specially tailored Genetic Algorithm (GA) approach for reinforcement learning has been proposed to optimize the ordinal structure fuzzy controller. …”
Get full text
Get full text
Get full text

Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

“…This is further worsen by the use of single sensors modality and machine learning algorithms. Furthermore, developing robust and efficient methods are required to handle issues such as orientation and position displacement, sensor fusion and feature incompatibility, automatic feature representation, and how to minimize intra-class similarity and inter-class variability. …”
Get full text
Get full text
Get full text

Detection of phishing websites using machine learning approaches by Farashazillah Yahya, Magnus Anai, Ryan Isaac W Mahibol, Sidney Allister Frankie, Rio Guntur Utomo, Chong Kim Ying, Eric Ling Nin Wei

“…The dataset consists of 11,055 observations and 32 variables. Three supervised learning models are implemented in this study: Decision Tree, K-Nearest Neighbour (KNN), and Random Forest. …”
Get full text
Get full text
Get full text
Get full text

Handover Management for Drones in Future Mobile Networks—a Survey by Ibraheem Shayea, Pabiola Dushi, Mohammed Banafaa, Rozeha A. Rashid, Sawsan Ali, Mohd Adib Sarijari, Yousef Ibrahim Daradkeh, Hafizal Mohamad

Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

“…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
Get full text
Get full text
Get full text
Get full text
Get full text

One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
Get full text
Get full text

Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
Get full text
Get full text

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. …”
Get full text
Get full text

Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
Get full text
Get full text
Get full text
Get full text

Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

“…In contrast, machine learning is used to calculate the accuracy assessment of dependent between independent variables. …”
Get full text
Get full text

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
Get full text
Get full text

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

Depression prediction using machine learning: a review by Abdul Rahimapandi, Hanis Diyana, Maskat, Ruhaila, Musa, Ramli, Ardi, Norizah

“…The aim of this study is to identify important variables used in depression prediction, recent depression screening tools adopted, and the latest machine learning algorithms used. …”
Get full text
Get full text
Get full text

Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
Get full text
Get full text