Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
(10)
(9)
Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
(15)
(9)
Publication Date
Thu Jan 30 2025
Journal Name
Iraqi Journal Of Science
Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
Complex detection
Evolutionary algorithm
Missing PPI
Modularity
Protein–protein interaction
Unreliable PPI.
Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
(10)
(4)
Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
(59)
(45)
Publication Date
Sun Mar 01 2020
Journal Name
Computer Networks
(8)
(5)
Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
(24)
(18)
Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
Artificial neural network
Shell-and-tube heat exchanger
Outlet temperatures
training
validation and testing
The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
(172)
(140)
Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
(249)
(204)
Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings