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This project uses Deep Q-Network(DQN) for job shop scheduling in Reinforcement learning, and the information is taken from the public data platform - http://people.brunel.ac.uk/~mastjjb/jeb/orlib/f…
The public benchmark instances of flexible job shop scheduling problem
Compromising productivity in exchange for energy-saving does not appeal to highly capitalized manufacturing industries. However, we might be able to maintain the same productivity while significant…
Library to support the creation of solutions that utilize Gene Expression Programming for Neural Networks (GEPNN). Built on top of the geppy open source library.
A GEP (gene expression programming) test aimed to search Pythagoras theorem
Gene expression programming based on Ferreira 2001 paper
Research on Optimizing Pair Trading by Gene Expression Programming Method
A prototype of gene expression programming based evolutionary audio synthesizer.
Natural Computing Algorithms: Gene Expression Programming
A repository used in the exploration and implementation of Gene Expression Programming
Gene Expression Programming implementation for solving OpenAI gym atari environments.
A Gene Expression Programming Implementation in Python generally for symbolic regression purposes
Evolutionary NAS with cellular encoding of gene expression programming
An interpretable deep-learning architecture of capsule networks for identifying cellular-type gene expression programs from single-cell RNA-seq data
Genetic Programming for expression tree and coefficient optimization
该项目用于对沪深300股票的预测，包括股票下载，数据清洗，LSTM 模型的训练，测试，以及实时预测
EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.
This project uses jqdata to forecast the price of Chinese stock. The methods used include LSTM, LSTM_CNN, CNN_ LSTM, AdaBoost, random forest, and using AdaBoost to integrate LSTM
Geppy explores formula generation for a given dataset. Although not optimal in training paradigm it offers a faster execution time.
GEP based evolutionary AI using Microsoft's Malmo platform, thesis project for my course on evolutionary computation and artificial life
The GEP-LR algorithm encodes a regression function in the LR model using GEP algorithm instead of using the maximum likelihood estimation based on a priori assumption of linearity
Self-Learning GEP to solve Symbolic Regression
Experiments in Evolutionary Algorithms (EA), Genetic Programming (GP), Gene Expression Programming (GEP)