TRX closing-price predictions reached 98.42% average accuracy over the latest 3-day evaluation period using a GA-optimized Ensemble model. #TRX #TRON #CryptoPrediction #EnsembleLearning #GeneticAlgorithm #AI

Our GA-optimized ENSEMBLE model hit a strong 95.82% average accuracy predicting KAS daily close prices from June 7-10! 📈💻📊 #KAS #CryptoPrediction #EnsembleLearning #GeneticAlgorithm #DataScience

HYPE daily close-price forecasting using a GA-optimized ARIMA model achieved an average prediction accuracy of 92.8% over the latest evaluation period. 📈 #HYPE #ARIMA #GeneticAlgorithm #GA #MachineLearning #TimeSeriesForecasting #CryptoAI #DataScience

🔥#FeaturePaper & #EditorsChoicePaper! 🖥️A Lightweight Learning-Based Approach for Online Edge-to-Cloud Service Placement 🔗Read at: mdpi.com/2079-9292/15/1/65# Authors from @KAU @QUBelfast @ericsson #EdgetoCloudComputing #OnlineServicePlacement #NeuralNetworks #GeneticAlgorithm

Chainlink (LINK) daily closing price forecasts generated using a GA-optimized ARIMA framework achieved an average accuracy of 91.7% over the latest evaluation period. #LINK #Chainlink #ARIMA #GeneticAlgorithm #MachineLearning #DataScience

🌾🤖 ШТУЧНИЙ ІНТЕЛЕКТ ДОПОМАГАЄ ТОЧНОМУ ЗЕМЛЕРОБСТВУ 📖 Читати статтю: journals.uran.ua/eejet/artic… #EEJET #Scopus #ArtificialIntelligence #MachineLearning #DeepLearning #UNet #PrecisionAgriculture #Agriculture #SatelliteImagery #Optimization #GeneticAlgorithm #Research #Innovation

#Article: "ELM-GA-Based Active Comfort Control of a Piggyback Transfer Robot" 👨‍🏫Authors: Liyan Feng, Xinping Wang, Teng Liu, Kaicheng Qi, Long Zhang, Jianjun Zhang, Shijie Guo 👉Paper link: mdpi.com/2075-1702/13/8/748 #NursingRobots #GeneticAlgorithm @MDPIEngineering @MDPIOpenAccess

Assessment of the potential for using PET waste as geomaterials in soil micro-reinforcement Read: sciencedirect.com/science/ar… #ArtificialIntelligence #GeneticAlgorithm #WaterTreatment #Catalysis #SustainableTechnology

✨Call for Reading ✨ Presenting GAELLLE: An Online Genetic Algorithm for Electronic Landscapes Exploration of Reactive Conformers 👥 Olivier Aroule, Fabien Torralba, Guillaume Hoffmann mdpi.com/3042-6723/1/1/1 #ComputationalChemistry #GeneticAlgorithm #AIChemistry

⚡ SUI daily forecasting powered by the GA-optimized XGBOOST model reached an average prediction accuracy of 96.92% in the latest 7-day performance test. AI continues to enhance crypto analytics 📈 #SUI #XGBOOST #GeneticAlgorithm #AI #CryptoPrediction #MachineLearning

#GeneticAlgorithm (GA) Intro with Example Code. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/GA-Algorithms References DataCamp. (2024, July 29). Genetic algorithm: Complete guide with Python implementation. DataCamp. Retrieved March 30, 2025, from datacamp.com/tutorial/geneti… Dr. Panda. (2020, September 20). What is genetic algorithm? Learn With Panda. Retrieved March 30, 2025, from learnwithpanda.com/2020/09/2… BotPenguin. (n.d.). Genetic algorithms in machine learning: Understanding the basics. BotPenguin. Retrieved March 30, 2025, from botpenguin.com/glossary/gene…

📈 ETH Daily forecast using GA LightGBM delivered strong results! Achieved ~94.5% accuracy comparing predicted vs actual closes over the past 7 days. Keeping the models sharp! 💪 #Ethereum #ETH #LightGBM #GeneticAlgorithm #Crypto #ETHPricePrediction

HBAR price prediction using GA-optimized ARIMA delivers ~95.77% accuracy 📈 Avg deviation ≈ 4.23%, showing reliable trend capture with minor bias. #HBAR #Hedera #Crypto #PricePrediction #ARIMA #GeneticAlgorithm #DataScience

📢 #highlycited paper 📚 #Robotic #CellLayout #Optimization Using a #GeneticAlgorithm 🔗 mdpi.com/2076-3417/14/19/860… 👨‍🔬 by Raúl-Alberto Sánchez-Sosa et al. 🏫 Centro de Tecnología Avanzada

#Article 📜 Dynamic Modeling and Analysis of Industrial Robots for Enhanced Manufacturing Precision by Claudius Birk, et al. mdpi.com/2076-0825/14/7/311 #industrialrobots #dynamicmodeling #parameteridentification #jointcompliance #transversestiffness #modalanalysis #geneticalgorithm

Deep Learning-Guided Evolutionary Optimization for Protein Design 1 BoGA introduces a hybrid approach combining genetic algorithms with Bayesian optimization, where a surrogate model acts as a discriminator to filter candidate sequences before expensive evaluation, dramatically improving optimization efficiency. 2 The key innovation lies in decoupling sequence generation from evaluation: the genetic algorithm proposes diverse candidates through mutation, while a deep learning surrogate model prioritizes which candidates merit costly structure prediction or docking calculations. 3 The framework demonstrates superior performance across multiple tasks including beta-sheet fraction optimization, normalized hydrophobic moment maximization, and AlphaFold-guided secondary structure design, with larger proposal pools consistently yielding better results. 4 In a real-world application, BoGA successfully designed peptide binders targeting pneumolysin, a critical virulence factor of Streptococcus pneumoniae, accelerating discovery of high-confidence binders compared to standard genetic algorithms. 5 The method offers significant advantages over existing approaches like hallucination or diffusion-based methods: no requirement for large-scale pre-training, flexible objective functions without retraining, and seamless integration of advancing structure prediction tools. 6 BoGA is implemented within the modular BoPep suite, supporting interchangeable embeddings, surrogate architectures, acquisition functions, and mutation operators, making it a generalizable strategy for diverse protein design objectives. 📜Paper: arxiv.org/abs/2603.02753 #ProteinDesign #BayesianOptimization #GeneticAlgorithm #DeepLearning #ComputationalBiology #PeptideBinders #Pneumolysin #Bioinformatics #AIforScience

In TRY mode: Bot executes simulated trades with fake 50 SOL Tracks positions & P&L in real-time Feeds outcomes to GeneticAlgorithm (evolves every 10 trades) Updates PatternMemory with results No real money, but learns from live market data

Designing a simple but robust #geneticalgorithm for weighted #setcover: “An Improved Genetic Algorithm for Set Cover using #RosenthalPotential” by Dena Tayebi, Saurabh Ray, Deepak Ajwani. ACSIS Vol. 39 p. 689–694; tinyurl.com/2v94ph7z

Just released version 9.0.0 of the #Jenetics #Java library. It now requires Java 25 to compile and run. #GeneticAlgorithm #EvolutionaryAlgorithm #GrammaticalEvolution #GeneticProgramming #MultiobjectiveOptimization #MOEA github.com/jenetics/jenetics…

Watch AI @TamauPogi @EvenepoelRemco @lizziedeignan @MarkCavendish @LauraKenny31 @NicoleCooke2012 battle it out (against Merckx and Indurain!) @BritishCycling @LeTour #geneticalgorithm #neuroevolution