PROJECT TITLE :

A Dynamic Multiagent Genetic Algorithm for Gene Regulatory Network Reconstruction Based on Fuzzy Cognitive Maps

ABSTRACT:

In order to reconstruct giant-scale gene regulatory networks (GRNs) with high accuracy, a robust evolutionary algorithm, a dynamic multiagent genetic algorithm (dMAGA), is proposed to reconstruct GRNs from time-series expression profiles based mostly on fuzzy cognitive maps (FCMs) during this paper. The algorithm is labeled as dMAGAFCM-GRN. In dMAGAFCM-GRN, agents and their behaviors are designed with the intrinsic properties of GRN reconstruction issues in mind. All agents live during a lattice-like atmosphere, and therefore the neighbors of each agent are changed dynamically consistent with their energy in each generation. dMAGAFCM-GRN can learn continuous states directly for FCMs from knowledge. Within the experiments, the performance of dMAGAFCM-GRN is validated on both large-scale artificial information and therefore the benchmark DREAM3 and DREAM4. The experimental results show that dMAGAFCM-GRN is ready to effectively learn FCMs with 200 nodes; that's, 40 00zero weights would like to be optimized. The systematic comparison with five existing algorithms shows that dMAGAFCM-GRN outperforms all different algorithms and will approximate the time series with high accuracy.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : A Novel Dynamic Model Capturing Spatial and Temporal Patterns for Facial Expression Analysis ABSTRACT: Incorporating spatial and temporal patterns present in facial behavior should substantially improve facial
PROJECT TITLE : Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images ABSTRACT: The use of kinetic modeling (KM) on a voxel level in dynamic PET pictures frequently results in large amounts of noise,
PROJECT TITLE : Robust Unsupervised Multi-view Feature Learning with Dynamic Graph ABSTRACT: By modeling the affinity associations with a graph to lower the dimension, graph-based multi-view feature learning algorithms learn a
PROJECT TITLE : Deep Tone Mapping Operator for High Dynamic Range Images ABSTRACT: The need for a rapid tone mapping operator (TMO) capable of adapting to a wide range of high dynamic range (HDR) content on low dynamic range (LDR)
PROJECT TITLE : Dynamic Scene Deblurring by Depth Guided Model ABSTRACT: Object movement, depth fluctuation, and camera shake are the most common causes of dynamic scene blur. For the most part, present approaches use picture

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry