Search alternatives:
processing algorithm » processing algorithms (Expand Search)
setting algorithm » scheduling algorithm (Expand Search)
per algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search), search algorithm (Expand Search)
elementi » elements (Expand Search), element (Expand Search), elemental (Expand Search)
processing algorithm » processing algorithms (Expand Search)
setting algorithm » scheduling algorithm (Expand Search)
per algorithm » deer algorithm (Expand Search), rd algorithm (Expand Search), search algorithm (Expand Search)
elementi » elements (Expand Search), element (Expand Search), elemental (Expand Search)
-
141
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…An integrated web application is developed to mock up the end-to-end process in ecommerce. Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
Get full text
-
142
-
143
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
Get full text
Get full text
-
144
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
-
145
-
146
Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
Published 2019Get full text
doctoralThesis -
147
A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
Get full text
Get full text
Get full text
Get full text
article -
148
Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…Analysis of the performance, on the same data-sets, reveals that the proposed GOAIT2FELM could be a better approach for improving the accuracy of the IT2-FLS as compared to other variants of the optimized IT2-FLS.…”
-
149
Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
Get full text
Get full text
Get full text
article -
150
-
151
-
152
Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
-
153
A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities
Published 2021“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”
-
154
Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”
-
155
Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…The proposed framework is flexible and general and can be applied to other greenhouses with different configurations and cultivated crops by fine-tuning it on the new data set.</p><h2>Other information</h2><p dir="ltr">Published in: Applied Energy<br>License:<a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher'swebsite: <a href="https://doi.org/10.1016/j.apenergy.2023.121190" target="_blank">https://doi.org/10.1016/j.apenergy.2023.121190</a><br><a href="http://dx.doi.org/10.2147/pgpm.s391394" target="_blank"></a></p>…”
-
156
-
157
Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare
Published 2007“…With all the preventive methods, malicious users still find new methods that overcome the system security, and access and modify the sensitive information. To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. …”
Get full text
Get full text
Get full text
article -
158
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Published 2021“…Connecting the ubiquitous sensing and big data processing of critical information in infrastructures through the IoT paradigm is the future of SHM systems. …”
Get full text
article -
159
-
160
Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control
Published 2021“…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …”