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Model Perspective
Model Perspective
Jan 30, 2026 · Fundamentals

Mastering Multi‑Dimensional Forecasting: From Peer Benchmarks to System‑Level Insights

This article presents a comprehensive framework for forecasting that combines peer (same‑level) comparison, bottom‑up decomposition, top‑down system thinking, time‑series analysis, causal modeling, and scenario simulation, while highlighting each method's strengths, limitations, and practical wisdom for effective decision‑making.

PredictionTime Seriescausality
0 likes · 12 min read
Mastering Multi‑Dimensional Forecasting: From Peer Benchmarks to System‑Level Insights
Data Party THU
Data Party THU
Oct 8, 2025 · Artificial Intelligence

How TrialBench Is Revolutionizing AI‑Driven Clinical Trial Prediction

TrialBench, an open multimodal AI‑ready dataset platform for clinical trial prediction, aggregates 23 sub‑datasets covering eight key tasks—from trial duration and patient dropout to adverse events and dosage recommendation—providing baseline models, evaluation metrics, and tools that bridge AI researchers and medical scientists.

Clinical TrialsPharmaPrediction
0 likes · 6 min read
How TrialBench Is Revolutionizing AI‑Driven Clinical Trial Prediction
Amap Tech
Amap Tech
Aug 28, 2025 · Artificial Intelligence

How AI Powers Real‑Time Bus and Subway Predictions in Smart Cities

This article explores how Gaode leverages AI and large‑scale spatio‑temporal pre‑training to transform uncertain urban transit into reliable, real‑time bus and subway predictions, detailing technical challenges, model architectures, and user‑focused features that enhance daily commuting.

GaodePredictionpublic transportation
0 likes · 7 min read
How AI Powers Real‑Time Bus and Subway Predictions in Smart Cities
Model Perspective
Model Perspective
Oct 16, 2024 · Fundamentals

Uncovering Hidden Assumptions: Using First Principles to Strengthen Article Readership Models

By applying first‑principles thinking to a simple article‑view model, this piece reveals how underlying assumptions about reader interest, platform recommendation, and social sharing drive observed readership decay, and demonstrates how deeper, theory‑grounded models can yield more reliable predictions.

Predictionfirst principlesmathematical modeling
0 likes · 8 min read
Uncovering Hidden Assumptions: Using First Principles to Strengthen Article Readership Models
Ctrip Technology
Ctrip Technology
Sep 29, 2024 · Artificial Intelligence

Structured Components-based Neural Network (SCNN) for Multivariate Time Series Forecasting: Theory, Implementation, and Business Application

This article presents the SCNN model for multivariate time series forecasting, explains its decomposition into long‑term, seasonal, short‑term, and co‑evolving components, details the neural‑network‑based fusion and loss design, provides Python code snippets, and demonstrates its practical deployment for business volume prediction at Ctrip.

Neural NetworkPredictionPython
0 likes · 30 min read
Structured Components-based Neural Network (SCNN) for Multivariate Time Series Forecasting: Theory, Implementation, and Business Application
Model Perspective
Model Perspective
Mar 16, 2024 · Artificial Intelligence

What Watching a TV Drama Reveals About AI Model Training and Learning Strategies

The article draws parallels between expert viewers dissecting the drama "The Legend of Zhen Huan," efficient paper‑reading techniques, and the active‑prediction plus contrast‑learning approach that underpins modern AI model training, highlighting how proactive thinking boosts both personal and machine learning outcomes.

AI trainingLarge Language ModelsPrediction
0 likes · 8 min read
What Watching a TV Drama Reveals About AI Model Training and Learning Strategies
Model Perspective
Model Perspective
Feb 1, 2024 · Artificial Intelligence

Discover Top Change & Prediction Model Articles for AI and Data Science

This article compiles a categorized list of recent model papers, covering change models and various prediction models—including time series, machine learning, gray prediction, and deep learning—providing direct references for students and researchers interested in AI and data‑driven modeling.

Artificial IntelligencePredictionTime Series
0 likes · 6 min read
Discover Top Change & Prediction Model Articles for AI and Data Science
Test Development Learning Exchange
Test Development Learning Exchange
Jan 26, 2024 · Artificial Intelligence

Data Mining Techniques for Marketing: Customer Segmentation, Purchase Prediction, Recommendation, and More with Python

This article introduces ten data‑mining applications for marketing—including customer segmentation, purchase forecasting, market‑basket analysis, churn prediction, sentiment analysis, response modeling, recommendation systems, brand reputation, competitive analysis, and public‑opinion monitoring—each illustrated with concise Python code examples.

Customer SegmentationPredictionPython
0 likes · 11 min read
Data Mining Techniques for Marketing: Customer Segmentation, Purchase Prediction, Recommendation, and More with Python
DataFunSummit
DataFunSummit
Oct 3, 2023 · Artificial Intelligence

Time Series Forecasting for NIO Power Swap Stations: Business Background, Challenges, Algorithm Practice, and Future Outlook

This article presents a comprehensive case study of NIO's Power swap‑station ecosystem, detailing the business context, key forecasting challenges, the evolution from classical statistical models to deep‑learning architectures with specialized embeddings, and the practical outcomes and future plans for improving prediction accuracy.

Deep LearningElectric VehicleEmbedding
0 likes · 16 min read
Time Series Forecasting for NIO Power Swap Stations: Business Background, Challenges, Algorithm Practice, and Future Outlook
Model Perspective
Model Perspective
Sep 16, 2023 · Fundamentals

Why Mathematical Modeling Matters: From Tumor Growth to Bridge Vibrations

Mathematical modeling transforms complex real-world phenomena into solvable equations, enabling predictions and insights across fields such as medicine, engineering, weather forecasting, and power systems, while highlighting model types, classifications, benefits, and challenges for researchers and engineers.

Predictionmathematical modelingscience
0 likes · 6 min read
Why Mathematical Modeling Matters: From Tumor Growth to Bridge Vibrations
Model Perspective
Model Perspective
Nov 8, 2022 · Fundamentals

Mastering Multiple Linear Regression: Theory, Estimation, and Prediction

This article explains the fundamentals of multiple linear regression, covering model formulation, least‑squares estimation of coefficients, statistical tests for significance, and how to use the fitted equation for accurate predictions and confidence intervals.

Least SquaresMultiple Linear RegressionPrediction
0 likes · 5 min read
Mastering Multiple Linear Regression: Theory, Estimation, and Prediction
ELab Team
ELab Team
Sep 15, 2022 · Game Development

How to Build Scalable Multiplayer Game Server Architecture and Sync Strategies

This article explains the evolution of multiplayer game server architectures, compares client‑server and P2P models, details communication via long‑lived sockets, and explores frame‑sync, state‑sync, prediction, reconciliation and interpolation techniques with a complete React + Socket.io demo.

PredictionReconciliationServer Architecture
0 likes · 18 min read
How to Build Scalable Multiplayer Game Server Architecture and Sync Strategies
Model Perspective
Model Perspective
Sep 5, 2022 · Fundamentals

Why Understanding Causal Relationships Is Crucial for Machine Learning

This article explains why causal inference matters beyond prediction, introduces potential outcomes notation, demonstrates how bias separates correlation from causation, and outlines the conditions under which observed differences can be interpreted as true causal effects.

BiasPredictioncausal inference
0 likes · 16 min read
Why Understanding Causal Relationships Is Crucial for Machine Learning
Model Perspective
Model Perspective
Aug 24, 2022 · Fundamentals

How the GM(1,N) Grey Model Predicts Multi‑Variable Systems

The GM(1,N) prediction model extends the classic GM(1,1) approach to multiple indicator variables by applying accumulated generating operations, forming a first‑order differential equation, converting it to a discrete model, and using least‑squares estimation to derive prediction values for each variable.

Multivariate ForecastingPredictionTime Series
0 likes · 2 min read
How the GM(1,N) Grey Model Predicts Multi‑Variable Systems
Model Perspective
Model Perspective
Jun 2, 2022 · Fundamentals

How Adaptive Filtering Optimizes Time Series Forecasting

Adaptive filtering predicts time series by iteratively adjusting weight coefficients based on prediction errors, using a learning constant to control adaptation speed, making it a simple yet powerful method that leverages all historical data for continuously improving forecasts.

PredictionSignal Processingadaptive filtering
0 likes · 4 min read
How Adaptive Filtering Optimizes Time Series Forecasting
Alimama Tech
Alimama Tech
Feb 23, 2022 · Artificial Intelligence

Meta‑Network Based Multi‑Scenario Multi‑Task Model (M2M) for Alibaba Advertising Merchants

The paper introduces a Meta‑Network based Multi‑Scenario Multi‑Task (M2M) model for Alibaba’s advertising merchants, combining a transformer‑driven backbone with scene‑aware meta‑learning modules to jointly predict spend, clicks and activity across diverse ad scenarios, achieving up to 27 % error reduction offline and over 2 % lifts in merchant activity and ARPU online.

AlibabaMeta LearningPrediction
0 likes · 14 min read
Meta‑Network Based Multi‑Scenario Multi‑Task Model (M2M) for Alibaba Advertising Merchants
Hulu Beijing
Hulu Beijing
Nov 10, 2020 · Artificial Intelligence

Hulu’s AI Secrets: Binge Ad Prediction and Real‑Time Allocation

On November 7, 2020, Hulu’s Shulei presented how the company’s video advertising platform employs AI-driven algorithms—including binge‑watch prediction, inventory forecasting with Prophet, and a PID‑controller based real‑time allocation system—to enhance targeting, optimize revenue, and improve user experience.

AdvertisingPredictionReal-Time
0 likes · 7 min read
Hulu’s AI Secrets: Binge Ad Prediction and Real‑Time Allocation
Meituan Technology Team
Meituan Technology Team
Jun 11, 2020 · Artificial Intelligence

Pedestrian Trajectory Prediction: Methodology and Experience from the ICRA 2020 TrajNet++ Competition

The ICRA 2020 TrajNet++ competition challenged teams to predict 4.8‑second pedestrian paths from 3.6‑second observations, and Meituan’s winning solution used a Seq2Seq world‑model that encodes past trajectories, updates a spatio‑temporal interaction map, and decodes future positions, achieving a 1.24 m final displacement error and demonstrating readiness for real‑world unmanned delivery.

ICRA 2020Predictionai
0 likes · 14 min read
Pedestrian Trajectory Prediction: Methodology and Experience from the ICRA 2020 TrajNet++ Competition
Amap Tech
Amap Tech
Jun 9, 2020 · Artificial Intelligence

Deep Learning Approach for Route ETA Prediction in Navigation

The article proposes a deep‑learning framework that uses an LSTM to predict segment‑level travel times and fully‑connected layers to aggregate them into a full‑route ETA, demonstrating on Beijing data a 28.2% MSE reduction and superior accuracy over traditional regressors by capturing temporal and network dependencies.

ETALSTMPrediction
0 likes · 7 min read
Deep Learning Approach for Route ETA Prediction in Navigation
Meituan Technology Team
Meituan Technology Team
Nov 21, 2019 · Artificial Intelligence

StarNet: Global Interaction Network for Pedestrian Trajectory Prediction

StarNet is a neural network for pedestrian trajectory prediction in large‑scale delivery, using a global dynamic map and a Hub‑Host architecture to model interactions efficiently, reducing complexity from O(N²) to O(N), and achieving higher accuracy with fast inference compared to baseline methods.

Deep LearningLSTMPrediction
0 likes · 15 min read
StarNet: Global Interaction Network for Pedestrian Trajectory Prediction
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 17, 2019 · Artificial Intelligence

How Association Rules and Machine Learning Reveal Stock Market Industry Linkages

This report analyzes 2018 AMAC industry index data using association‑rule mining and several machine‑learning models (Apriori, KNN, Bayesian, decision tree, neural network) to uncover sector linkages, predict index and stock movements, compare model performance, and suggest future improvements.

PredictionR languageassociation rules
0 likes · 11 min read
How Association Rules and Machine Learning Reveal Stock Market Industry Linkages
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 12, 2018 · Artificial Intelligence

How Alibaba’s ‘Ali Xiaomi’ Prediction Platform Boosts Smart Customer Service with AI

Alibaba’s Ali Xiaomi prediction platform leverages AI techniques—including order and issue prediction, deep CTR models, reinforcement learning, and streaming computation—to proactively anticipate user intents, improve click‑through, resolution and satisfaction rates across multiple chatbot services, while addressing code duplication and model deployment challenges.

PredictionStreamingai
0 likes · 14 min read
How Alibaba’s ‘Ali Xiaomi’ Prediction Platform Boosts Smart Customer Service with AI
Tencent Cloud Developer
Tencent Cloud Developer
Oct 11, 2018 · Artificial Intelligence

Demystifying Neural Networks: A Mathematical Approach (Part 1)

The article mathematically demystifies neural networks by first illustrating a linear predictor for kilometre‑to‑mile conversion and a basic bug classifier, then exposing the limits of single linear boundaries (e.g., XOR), before introducing artificial neurons, activation functions, and multi‑layer weight‑adjustment training.

Artificial NeuronPredictionactivation functions
0 likes · 15 min read
Demystifying Neural Networks: A Mathematical Approach (Part 1)
JD Tech
JD Tech
Sep 29, 2018 · Artificial Intelligence

JD.com Prediction Technology: Architecture, Applications, and Future Directions

The article outlines JD.com's evolution of prediction technology from early book‑category sales forecasting to a comprehensive AI‑driven platform that supports sales, order, and GMV forecasts, describes its modular architecture and core algorithm choices, and discusses future enhancements for smarter supply‑chain collaboration.

Big DataPredictionforecasting
0 likes · 6 min read
JD.com Prediction Technology: Architecture, Applications, and Future Directions
ITPUB
ITPUB
Jun 15, 2018 · Fundamentals

Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis

Using a Kaggle dataset of over 40,000 matches from 1872 to 2018, this notebook demonstrates how to clean, transform, and visualize World Cup data with Python, pandas, and Matplotlib to identify top‑winning teams, total goal statistics, and forecast the most likely 2018 champion.

Jupyter NotebookPredictiondata-analysis
0 likes · 11 min read
Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis
Ctrip Technology
Ctrip Technology
Dec 27, 2017 · Artificial Intelligence

Intelligent Outbound Call Automation for Hotel Order Confirmation at Ctrip

This article describes how Ctrip’s data science team applied machine learning models to predict response times and outbound call effectiveness, transforming the hotel order confirmation process into an intelligent, automated workflow that reduces unnecessary calls, improves resource allocation, and boosts overall call‑center efficiency.

CtripPredictionai
0 likes · 9 min read
Intelligent Outbound Call Automation for Hotel Order Confirmation at Ctrip
Efficient Ops
Efficient Ops
Apr 14, 2016 · Big Data

Why Big Data May Not Be the Gold Mine You Expect: Insights and Pitfalls

The article examines what big data really means, its core 4 V characteristics, current limitations in China, the overhyped value of data, the importance of business‑driven applications, and why starting from small, relevant data is essential for true predictive power.

Big DataBusiness IntelligenceData Value
0 likes · 13 min read
Why Big Data May Not Be the Gold Mine You Expect: Insights and Pitfalls
Baidu Tech Salon
Baidu Tech Salon
Aug 18, 2014 · Big Data

Big Data and Prediction: Insights from Baidu Research Lab

At Baidu’s 53rd Technology Salon, researcher Shen Zhiyong outlined the lab’s vision of an online intelligent system that unifies monitoring, anomaly detection, diagnosis and big‑data‑driven prediction—using time‑series, causal and simulation analyses—to forecast tourism crowds, predict Gaokao essay topics, and illustrate both the opportunities and challenges of processing massive, heterogeneous data for real‑time decision support.

BaiduPredictionTime Series Analysis
0 likes · 8 min read
Big Data and Prediction: Insights from Baidu Research Lab
Baidu Tech Salon
Baidu Tech Salon
Aug 16, 2014 · Big Data

Big Data Prediction Practices: Baidu Technology Salon #53

At Baidu’s Technology Salon #53 on August 16, a near‑full audience heard data scientist Shen Zhiyong explain the origins of Baidu’s tourist‑flow prediction tool and Liu Ying discuss the evolution of social‑economic forecasting from classic “beer‑and‑diapers” models to modern big‑data analytics, followed by an interactive Q&A and prize‑giving session.

BaiduPredictionTechnology Salon
0 likes · 4 min read
Big Data Prediction Practices: Baidu Technology Salon #53