Search Results - (( data normalization _ algorithm ) OR ( sequence optimization sensor algorithm ))
Search alternatives:
- optimization sensor »
- data normalization »
- sensor algorithm »
-
1
An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks
Published 2017“…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
Get full text
Get full text
Get full text
Article -
2
A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network
Published 2016“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
Get full text
Get full text
Thesis -
3
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
Get full text
Get full text
Thesis -
4
-
5
Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. Deep learning algorithms were widely used among all the data-driven algorithms. …”
Get full text
Get full text
Get full text
Article -
6
Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…There were also attempts to hybridize SKF with other famous algorithms such as Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Sine Cosine Algorithm (SCA) to improve its performance. …”
Get full text
Get full text
Get full text
Get full text
Conference or Workshop Item -
7
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
Get full text
Get full text
Get full text
Thesis -
8
Effect of normalization and effect of normalization and training algorithm on radial basis training algorithm on radial basis function network performance function network performa...
Published 2007“…To recognize the effect of normalization of data and training algorithm on Radial Basis Function (RBF) performance.…”
Get full text
Get full text
Conference or Workshop Item -
9
An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
Get full text
Get full text
Conference or Workshop Item -
10
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Get full text
Thesis -
11
-
12
Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…This N4SID plays the role of the software sensor for on-line estimation of prediction matrices and control matrices of the bioprocess, joint together with model predictive control (MPC) in order to obtain the optimal control sequence. …”
Get full text
Get full text
Conference or Workshop Item -
13
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Monograph -
14
An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
Get full text
Get full text
Get full text
Thesis -
15
Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural
Published 2006“…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
Get full text
Get full text
Monograph -
16
-
17
Algorithm for calculation of cephalometric soft tissue facial traits
Published 2007“…The source data used to get 3D digital models of human soft tissues include CT data and 3D laser scanner data. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
18
Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
Published 2021“…This research contributes to the world of health, where we classify the Electrocardiogram (ECG) data, so that it can classify abnormal and normal cardiac disorders using the Fuzzy Cognitive Map (FCM) algorithm.…”
Get full text
Get full text
Conference or Workshop Item -
19
Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
Get full text
Get full text
Thesis -
20
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
Get full text
Get full text
Get full text
Get full text
Thesis
