Titlebook: Advances in Computational Intelligence; 23rd Mexican Interna Lourdes Martínez-Villase?or,Gilberto Ochoa-Ruiz Conference proceedings 2025 Th

使入迷

Change Management und Innovation challenge lies in effectively exploring both the goal and state spaces. We introduce an agent, LAtent QUantized eXplorative Achiever (LAQUAXA), that enables structured exploration process constructing the world model with two improving features: learnable first state distribution and quantization?o

洞穴

Change Management und Innovationultural runoff. This study applied machine learning (ML) techniques to predict and classify contaminant presence in Mexican water bodies using publicly available datasets. The objectives were to collect and analyze water quality data, develop predictive models, implement ML algorithms?for classifica

GRE

Change Management und Innovationnd disaster management. In recent months, Mexico has experienced severe droughts and?high temperatures, which has further highlighted the necessity?for reliable weather forecasting. This article presents a weather predictor model tailored for Mexico, which employs satellite imagery and Convolutional

陰謀小團(tuán)體

Grundbegriffe und Managementprozessience against climate change. Data from Mexico City (CDMX), State of Mexico (EDOMEX), and Morelos, including precipitation, temperature, soil water, surface water,?and underground water levels, was collected, normalized and treated using data tidying techniques. The combined datasets were analysed u

和諧

absolve

Die Grundlagen der Marketing-Konzeption,ks, to forecast water levels?at the Lago de Chapala Dam. The research highlights the importance?of integrating a 1-day lag feature to provide temporal context, significantly enhancing model performance. Analyzing daily records from 1991 to 2024, including variables like precipitation, evaporation, a

悶熱

figment

Grundlagen und Prozess der Marktforschungher. In the competitive world?of coffee shops, providing enticing and customized product combinations is crucial for enhancing customer experience and building loyalty. We utilized a newly generated transactional database from a coffee shop franchise in Mexico to identify unique itemsets using?a sta

indices

Analyse der strategischen Ausgangssituation the application of different machine learning algorithms to develop an automated trading system for?the ETF ‘QQQ’ (which is a tracker of the NASDAQ-100 Index). Our aim?is to build a model capable of consistently generating positive returns over time by predicting buy and sell signals that help the

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