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Intrusion Detection System(IDS) Input Features Prediction Model Factor Analysis Logistics Service Response Time Prediction Performance Traffic Forecasting Feature Engineering Internal And External Detection Rate(DR) Clustering Analysis Parcel Logistics Detection Performance Delivery Service Data Sets Fast Detection Load Analysis Multiple Regression Prediction Problem Event Prediction Feature Space Staff Scheduling Part-Time Operational Optimization Operation Plan Detection Efficiency Logistics Operation Detection Model Extreme Event Self-Organizing Map Scheduling Flexibility Detection Process K-Means Clustering Technique Second Phase Prediction Accuracy Balancing And Scheduling Service Productivity Service Organization Load Scheduling Demand Prediction Computationally Efficient Regression Model Multiple Categories Feature Selection Method Ensemble Method Service Sector Data-Driven Forecasting Demand Hierarchical Feature Hierarchical Detection Logistics System Multi-Functional Service Reliability Weighted Ensemble Scheduling Problem Traffic Pattern Ensemble Model Feature Selection Algorithm Forecasting Model Hybrid Prediction Low Computational Cost Multilayer Perceptron Normal Pattern Short-Term Prediction Support Vector Regression(SVR) Parameter Adjustment Traffic Prediction Estimation Method Feature Reduction Misuse Detection Multi-Category Real-Time Intrusion Detection South Korea Weight Vector Unsupervised Anomaly Detection Third Phase Construction Scheme Detection Accuracy Dimensionality Reduction Demand Forecasting Forecasting Performance History Data Hierarchical Approach Machine Learning Approach Model-Based Supply Chain Management(SCM) Scientific Workflows Planning And Scheduling Workforce Scheduling Hybrid Models Large-Scale Level 5 Multinomial Logistic Regression Model Selection Reduction Algorithm Self-Similarity Principal Components Analysis(PCA) Prediction System Predictive Model Volume-Based Weighted Average Anomaly Detection System Comparative Study Data Space Delivery Time Error Rate Kdd Cup 1999 Logistic Operations Detection Method Regression-Based Random Forest Runtime Prediction Similarity Analysis Service Quality Optimal Operating Clustered Data Case Studies Diagnostic Model Event Forecasting Experimental Study Hierarchical Clustering Key Characteristics Labor Intensiveness Parallel System Accuracy And Efficiency On-Site Computational Complexity Data Patterns Feature Construction High-Capacity Low Time Complexity Lean Six Sigma Network Traffic Data Reduced Feature Hybrid Feature Selection Statistical Features Parallel Applications Workload Balancing Workflow Support Unsupervised Learning