jackishappy

jackishappy's Stars

• Krisna-Sah-Teli/PROCESS-OPTIMIZATION-PIPE-NETWORK-DESIGN-ANALYSIS

  This is an application of Process Optimization to optimize the cost incurred on pipe distribution for water supply in large scale within the constraints of radius of pipe, water flow rate and height of buildings.

  Language:MATLAB21

• Jetina/MGPSLPSO

  MGP-SLPSO main code

  Language:MATLAB3

• leoclassic/RNN_LSTM

  Matlab Mex implementation

  Language:Matlab1

• NiloofarShahbaz/PSOClustering

  This is an implementation of clustering IRIS dataset with particle swarm optimization(PSO)

  Language:Python183

• dandynaufaldi/particle-swarm-optimized-clustering

  Hybrid PSO Clustering Algorithm with K-Means for Data Clustering

  Language:Jupyter Notebook4727

• ratral/sensor_placement

  Sensor placement for leak detection and location in water distribution networks with EPANET

  Language:R8

• huayuanmay/TDOA

  Unmanned aerial vehicle (UAV) plays an extremely important role in the current military warfare because of their low cost, zero casualties, flexibility and sustainable operations. The passive TDOA positioning system requires only a single receiving channel for each observation station, which can minimize the load requirements of the positioning system, and has high positioning accuracy. It is widely used in military fields such as electronic countermeasures. In this thesis, the problem of time difference location of radar signals based on UAVs is studied.

  31

• byq-luo/PSO-DBN

  By using 3-layer DBN to extract features embed in original image data, then fed the features into a extreme learning machine(ELM) for classification. Due to the difficulty in hiiden-nodes selection， then PSO was applied to select it automatically ,and PSO aimed to minimize the fitness function that is the accuracy of DBN-ELM crossvalidation classifcition

  75

• zhang271018/fpga

  TDOA-FPGA

  Language:VHDL3

• CyberLympha/CISS

  Preparation to CISS-2022 competition in Singapour

  Language:Jupyter Notebook21

• pirofex/ml-nids-industrial-paper

  Language:Python1

• Aegrah/AE-VAE-PCA-Anomaly_Detection-ML

  Anomaly Detection in OT datasets through machine learning (AE/VAE/PCA)

  Language:Jupyter Notebook2

• nosyarlin/Cyber-Attack-Prediction

  Modern water distribution systems rely on computers, sensors and actuators for both monitoring and operational purposes. This combination of physical processes and embedded systems—cyber-physical systems, in short—improves the level of service of water distribution networks but exposes them to the potential threats of cyber attacks. We will be using statistical models to attempt to detect cyber attacks.

  Language:Jupyter Notebook2110

• mnguyen0226/caia_cyberbiosecurity

  Dataset for Governors School for Agriculture (CAIA 2022) at Virginia Tech

  1

• mnguyen0226/cbs_workshop_vt

  Guest Speaker - Governors School for Agriculture (CAIA 2022) at Virginia Tech

  Language:Jupyter Notebook2

• mnguyen0226/tsgans_cps

  TimeGANs for synthetic data generation in cyber-physical systems using Tensorflow

  Language:Jupyter Notebook82

• a1708192/WDSOP

  Covariance Matrix Adaptation Greedy Search Applied to Water Distribution System Optimization

  Language:MATLAB22

• neelabhsinha/Leakage-Detection-in-Smart-Water-Distribution-Systems

  This repository contains the coding aspect of the project Leakage Detection in Smart Water Distribution Systems, where the collected data is used for training an ANN model to detect leakage.

  Language:Jupyter Notebook74

• glorialulu/GNN_StateEstimation_WDS

  Graph neural networks for state estimation in water distribution systems

  Language:Jupyter Notebook2810

• OpenWaterAnalytics/EPANET

  The Water Distribution System Hydraulic and Water Quality Analysis Toolkit

  Language:C281205

• absaw/Surface-Water-Quality-Data-Anomaly-Detection

  Surface water quality data analysis and prediction of Potomac River, West Virginia, USA. Using time series forecasting, and anomaly detection : ARIMA, SARIMA, Isolation Forest, OCSVM and Gaussian Distribution

  Language:Jupyter Notebook148

• JedMills/MTFL-For-Personalised-DNNs

  Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.

  Language:Python8520

• revenol/WPMEC

  Deep Neural Network for Computation Rate Maximization in Wireless Powered Mobile-Edge Computing System

  Language:Python4928

• sumit521/Profit_Optimization_MEC

  Language:MATLAB192

• Ashwin0794/masters-thesis

  Energy Aware Resource Scheduling based on Genetic Algorithm in Edge Computing

  Language:Java5

• sangwoomoon/multiple_UAVs

  Hierarchical multi-agent systems for multiple UAVs

  Language:Matlab7721

• bilibili30/UAV-task-allocation-PSO

  基于粒子群算法多无人机任务分配

  Language:Python10310

• BillyMazotti/uav_trajectory_coverage

  Using OpenStreetMap (organized by MyGeoData) data to model building, customer, and vendor locations in San Francisco, New York City, and Los Angeles and determine the required number of randomly distributed sensors to achieve a desired trajectory coverage portion for various path planning algorithms (straight-line, RRT*).

  Language:MATLAB81

• stonecoder19/UMP

  UAV Mission Planner-Plans Optimal Route for a UAV of limited sensor range to scan an area given limited time and resources

  Language:Python71

• garg-akash/OverlapGaussian_LinearApproximation

  Trajectory Optimization for Drones along with obstacle avoidance using Overlap of Gaussian distributions

  Language:Matlab1