Search alternatives:
algorithm rate » algorithm fa (Expand Search), algorithm a (Expand Search), algorithm aoa (Expand Search)
rate function » taste function (Expand Search)
algorithm b » algorithm _ (Expand Search), algorithm a (Expand Search), algorithms _ (Expand Search)
algorithm rate » algorithm fa (Expand Search), algorithm a (Expand Search), algorithm aoa (Expand Search)
rate function » taste function (Expand Search)
algorithm b » algorithm _ (Expand Search), algorithm a (Expand Search), algorithms _ (Expand Search)
-
61
Regression testing web services-based applications
Published 2006“…Moreover, modifications handled by the algorithm are classified into three classes: (a) adding an operation, (b) deleting an operation, (c) fixing a condition or an action. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
62
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
doctoralThesis -
63
-
64
-
65
Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility
Published 2019“…We present performance results for the algorithm as a function of various system parameters assuming a random walk mobility model. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
66
Fragment based protein structure prediction. (c2013)
Published 2016“…The results, evaluated on three proteins, show that the algorithm produces tertiary structures with promising root mean square deviations, within reasonable times.…”
Get full text
Get full text
masterThesis -
67
Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
-
68
-
69
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
Get full text
Get full text
-
70
Impact of fuzzy volume fraction on unsteady stagnation-point flow and heat transfer of a third-grade fuzzy hybrid nanofluid over a permeable shrinking/stretching sheet
Published 2024“…Also, the comparison of Al<sub>2</sub>O<sub>3</sub>/SA, Cu/SA and Al<sub>2</sub>O<sub>3</sub> +Cu/SA through the fuzzy membership functions (MFs). The fuzzy MFs show that the hybrid nanofluid (Al<sub>2</sub>O<sub>3</sub> +Cu/SA) in terms of rate of heat transfer is better than both Cu/SA and Al<sub>2</sub>O<sub>3</sub>/SA nanofluids.…”
-
71
Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing
Published 2023“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”
-
72
Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…The research note is presented in two parts: Part A presents an overview of REBUS, including its development, algorithm, and its primary functions. Part B demonstrates the application of REBUS in examining a validated tourism model of destination image, satisfaction, and destination loyalty. …”
Get full text
Get full text
Get full text
Get full text
article -
73
Genetic Fuzzimetric Technique (GFT)
Published 2012Get full text
Get full text
Get full text
Get full text
conferenceObject -
74
Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks
Published 2018“…We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.…”
Get full text
Get full text
Get full text
Get full text
article -
75
Blood Glucose Regulation Modelling and Intelligent Control
Published 2024Get full text
doctoralThesis -
76
Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network
Published 2020“…An ANN model consists of three layers, 15 neutrons and 260 <i>epochs</i> accurately predict the CMP with 99.1% of data within ±10% deviation of the mean experimental value. …”
-
77
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…A tailored multi-term reward function is structured to penalize excessive yaw rate error, sideslip angle, tire slip deviations beyond peak grip regions, and power losses based on a realistic electric machine efficiency map. …”
-
78
Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces
Published 2021“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
-
79
DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
Published 2024“…The system comprises four VLC access points with light fixtures, reinforced by a mirror array sheet, and a mmWave access point with antennas, supported by a reflecting unit sheet. Within the system, both sheets function as IRS. The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. …”
-
80
Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. …”