書目名稱Advances in Computational Intelligence影響因子(影響力)學(xué)科排名
書目名稱Advances in Computational Intelligence網(wǎng)絡(luò)公開度
書目名稱Advances in Computational Intelligence網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Advances in Computational Intelligence被引頻次
書目名稱Advances in Computational Intelligence被引頻次學(xué)科排名
書目名稱Advances in Computational Intelligence年度引用
書目名稱Advances in Computational Intelligence年度引用學(xué)科排名
書目名稱Advances in Computational Intelligence讀者反饋
書目名稱Advances in Computational Intelligence讀者反饋學(xué)科排名
作者: BLANC 時(shí)間: 2025-3-21 23:40
Advances in Computational Intelligence978-3-031-75540-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Noctambulant 時(shí)間: 2025-3-22 03:07 作者: 離開就切除 時(shí)間: 2025-3-22 07:17 作者: 腐敗 時(shí)間: 2025-3-22 09:11
Price Estimation for?Pre-owned Vehicles Using Machine LearningThis article presents the initial analysis of pre-owned car pricing using machine learning techniques. We explore?three approaches: classic linear regression, tree boosting, and quantile regression algorithms. The scope of the article includes comparing these models and understanding the underlying data structure.作者: Climate 時(shí)間: 2025-3-22 15:35
Analysis of Predictive Factors in University Dropout Rates Using Data Science TechniquesThis study uses advanced data science techniques?to explore the variables that influence university dropout rates. Through predictive models and the integration of demographic, socioeconomic, and academic data, key factors are identified?and risk estimates are provided, with the goal of guiding interventions to improve student retention.作者: Paradox 時(shí)間: 2025-3-22 17:42 作者: 神圣不可 時(shí)間: 2025-3-23 00:22 作者: 可能性 時(shí)間: 2025-3-23 04:02
https://doi.org/10.1007/978-3-658-41918-9nt. Outdoor landscaping typically represents 40–70% of total water household consumption in some semi-arid areas; thus, outdoor water use is a significant factor that contributes to urban water sustainability..Evapotranspiration (ET) indicates the water and energy exchange between the atmosphere and作者: 上流社會(huì) 時(shí)間: 2025-3-23 08:09 作者: 使入迷 時(shí)間: 2025-3-23 12:26
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作者: 洞穴 時(shí)間: 2025-3-23 17:00
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作者: GRE 時(shí)間: 2025-3-23 18:06
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作者: 陰謀小團(tuán)體 時(shí)間: 2025-3-23 22:46
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作者: 和諧 時(shí)間: 2025-3-24 03:46 作者: absolve 時(shí)間: 2025-3-24 10:07
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作者: 悶熱 時(shí)間: 2025-3-24 12:33 作者: figment 時(shí)間: 2025-3-24 15:13
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作者: indices 時(shí)間: 2025-3-24 20:23
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 作者: 磨坊 時(shí)間: 2025-3-25 01:05 作者: SUE 時(shí)間: 2025-3-25 06:35
Datenanalyse und -interpretationproaches utilizing different?AI techniques, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), style-based generators, transformers, and diffusion models, have become popular for producing high-quality and diverse images. However, while humans can naturally assess?the作者: conscribe 時(shí)間: 2025-3-25 08:59
Analyse der strategischen Ausgangssituationtify predefined objects, only a few are applicable for real-time navigation in unfamiliar terrains. A key issue is the efficient selection of a minimum set of landmarks for localization. As humans, we often rely on natural landmarks in our environment before resorting to GPS, such as a house of a ce作者: aerobic 時(shí)間: 2025-3-25 13:11
https://doi.org/10.1007/978-3-658-29638-4ing, shorter hospitalization, and?less post-operative pain. Despite these advantages, laparoscopic procedures present challenges including limited vision?and maneuverability of surgical tools, requiring advanced assistive technologies. This paper presents a comparative study of?three state-of-the-ar作者: 幻影 時(shí)間: 2025-3-25 18:27
0302-9743 ce, MICAI 2024, held in Tonantzintla, Mexico in October?21–25, 2024...The 37 full papers presented in these proceedings were carefully reviewed and selected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections:..Part I -?Machine Learning; Co作者: Carcinoma 時(shí)間: 2025-3-25 21:38 作者: 割公牛膨脹 時(shí)間: 2025-3-26 03:57
Conference proceedings 2025m 141 submissions. The papers presented in these two volumes are organized in the following topical sections:..Part I -?Machine Learning; Computer Vision...Part II -?Intelligent Systems;?Bioinformatics and Medical Applications;?Natural Language Processing..作者: 做作 時(shí)間: 2025-3-26 06:37
0302-9743 lected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections:..Part I -?Machine Learning; Computer Vision...Part II -?Intelligent Systems;?Bioinformatics and Medical Applications;?Natural Language Processing..978-3-031-75539-2978-3-031-75540-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 刺激 時(shí)間: 2025-3-26 10:29 作者: GONG 時(shí)間: 2025-3-26 12:54 作者: 摘要 時(shí)間: 2025-3-26 18:47 作者: MOAN 時(shí)間: 2025-3-26 23:31
Talent Identification in Football Using Supervised Machine Learningother valuable insights gleaned from the results pave the way for further research endeavors. The study aims to encourage the adoption of advanced?data analytics and statistical methods within football clubs worldwide.作者: GRACE 時(shí)間: 2025-3-27 02:45 作者: 嬰兒 時(shí)間: 2025-3-27 05:51
Conference proceedings 20252024, held in Tonantzintla, Mexico in October?21–25, 2024...The 37 full papers presented in these proceedings were carefully reviewed and selected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections:..Part I -?Machine Learning; Computer Vis作者: senile-dementia 時(shí)間: 2025-3-27 12:35 作者: 轉(zhuǎn)換 時(shí)間: 2025-3-27 16:33
Latent State Space Quantization for Learning and Exploring Goals maximum volume of seen states while simultaneously exploring to acquire?new knowledge about the environment. Through experiments, we demonstrate the effectiveness of the proposed framework in multi-goal learning across diverse domains: continuous and discrete mazes. We found?that our approach surpa作者: 上下連貫 時(shí)間: 2025-3-27 20:50 作者: Estimable 時(shí)間: 2025-3-28 00:39 作者: 細(xì)胞膜 時(shí)間: 2025-3-28 02:54
Machine Learning Implementation for Water Quality Monitoring in the Desert State of Sonoraand poorly maintained, making it an imperfect source of information. Nonetheless, important insights?are extracted, such as the evolution of contamination over time,?which reveals how contamination-free water has become more scarce,?even reaching a point where there are no samples of high-quality wa作者: 軍械庫 時(shí)間: 2025-3-28 08:04
Predicting Water Levels Using Gradient Boosting Regressor and LSTM Models: A Case Study of Lago de Crning models into water resource management to improve prediction accuracy and ensure sustainable water supply and disaster readiness. The study aims to develop and validate predictive models, evaluate their accuracy and reliability, and provide insights for integrating these models into water manag作者: 拍下盜公款 時(shí)間: 2025-3-28 12:05
Efficiently Mining High Average Utility Co-location Patterns Using Maximal Cliques and Pruning Strats. First, neighboring instances are enumerated by using maximal cliques,?and then they are further arranged into a specified two-level hash?table structure. The keys in the first level are the initial possible candidates and the values are another hash table structure with?keys that are spatial feat作者: 草本植物 時(shí)間: 2025-3-28 14:35 作者: 慟哭 時(shí)間: 2025-3-28 19:13
Incremental Learning for Object Classification in a Real and Dynamic Worldntal classifier?which uses support vector machines and a novel strategy based on distance between distributions to identify new classes. The proposed approach was tested against other incremental learning approaches and in?real open-world conditions with promising results.作者: Platelet 時(shí)間: 2025-3-29 01:04
Easy for Us, Complex for AI: Assessing the Coherence of Generated Realistic Imagesshable from real-world scenes. This follows Moravec’s paradox, which states that tasks easy for humans, such as pattern recognition, are often difficult for computers, which proves?that the search for realism metrics keeps going. Specifically,?this review discusses how the coherence of generated rea作者: ANNUL 時(shí)間: 2025-3-29 04:10 作者: Pillory 時(shí)間: 2025-3-29 07:57 作者: FOLD 時(shí)間: 2025-3-29 13:39 作者: 傻瓜 時(shí)間: 2025-3-29 18:14 作者: AXIOM 時(shí)間: 2025-3-29 21:28
Change Management und Innovation identifying related groups to guide monitoring efforts. A decision tree classifier assessed the significance of features in predicting water quality and found ’Fecal coliforms’ to be the most crucial, achieving an accuracy of 99.99%. Additionally, Random Forest, Support Vector Machine, and AdaBoost作者: custody 時(shí)間: 2025-3-30 03:48 作者: Euphonious 時(shí)間: 2025-3-30 05:49 作者: bifurcate 時(shí)間: 2025-3-30 12:12
Die Grundlagen der Marketing-Konzeption,rning models into water resource management to improve prediction accuracy and ensure sustainable water supply and disaster readiness. The study aims to develop and validate predictive models, evaluate their accuracy and reliability, and provide insights for integrating these models into water manag作者: elucidate 時(shí)間: 2025-3-30 13:57
https://doi.org/10.1007/978-3-322-83529-1s. First, neighboring instances are enumerated by using maximal cliques,?and then they are further arranged into a specified two-level hash?table structure. The keys in the first level are the initial possible candidates and the values are another hash table structure with?keys that are spatial feat作者: Nebulous 時(shí)間: 2025-3-30 16:43
Analyse der strategischen Ausgangssituation (PCA). The models are trained and evaluated using cross-validation?and hyper-parameter tuning via Grid Search. Our results indicate?that XGBoost shows the highest return of 34.13 percent over the?test period. The Random Forest algorithm demonstrates the highest accuracy with an f1-score of 0.744. T作者: gerontocracy 時(shí)間: 2025-3-30 22:04
Grundlagen des strategischen Marketingntal classifier?which uses support vector machines and a novel strategy based on distance between distributions to identify new classes. The proposed approach was tested against other incremental learning approaches and in?real open-world conditions with promising results.作者: endarterectomy 時(shí)間: 2025-3-31 04:12
Datenanalyse und -interpretationshable from real-world scenes. This follows Moravec’s paradox, which states that tasks easy for humans, such as pattern recognition, are often difficult for computers, which proves?that the search for realism metrics keeps going. Specifically,?this review discusses how the coherence of generated rea作者: pessimism 時(shí)間: 2025-3-31 06:47 作者: 形狀 時(shí)間: 2025-3-31 12:16 作者: conception 時(shí)間: 2025-3-31 16:47
Towards Estimating Water Consumption in Semi-arid Urban Landscaping: A Machine Learning Approachnt. Outdoor landscaping typically represents 40–70% of total water household consumption in some semi-arid areas; thus, outdoor water use is a significant factor that contributes to urban water sustainability..Evapotranspiration (ET) indicates the water and energy exchange between the atmosphere and作者: chondromalacia 時(shí)間: 2025-3-31 19:00
Talent Identification in Football Using Supervised Machine Learningas consistently translated into?a significant competitive advantage throughout the history of?the sport..This study delves into this domain by comparing the performance?of three supervised machine learning models. The models were trained using a comprehensive dataset encompassing data for 1,086?male作者: ANN 時(shí)間: 2025-4-1 01:37
Latent State Space Quantization for Learning and Exploring Goals 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作者: 公式 時(shí)間: 2025-4-1 03:24 作者: 角斗士 時(shí)間: 2025-4-1 08:13
A ConvLSTM Approach for the WorldClim Dataset in Mexicond 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
