Flowchart of algorithm principles. by Wenjuan Zhou (115285)

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General architecture of XGBoost algorithm. by Saghir Ahmed (4416544)

Hyperparameters optimization of XGBoost algorithm. by Saghir Ahmed (4416544)

Multi-step prediction error. by Yubo Zhao (3873457)

“…Compared with other studies, we innovatively improved the prediction accuracy of the model significantly through noise removal and the introduction of multi-source features.…”

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. by Burak Alakent (463512)

Algorithm steps for house price prediction model. by Xuan Wang (55634)

“…The research problem is addressed by introducing the House Price Evaluation Model (HPEM), which utilizes a hybrid deep learning network for analyzing multi-source geographic data. The network integrates the attention mechanism with spatial feature extraction, and a bat optimization algorithm is used to improve explainability and accuracy. …”

Table 4 - A new design of wind power prediction method based on multi-interaction optimization informer model by Wenjuan Zhou (115285)

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Framework of STH-Trans model, from the multi-source data as fundamental input (bottom of the entire framework) to the spatiotemporal views adjustment (top of the framework). by Qun Zhao (603175)

Data sources for calibration and evaluation. by Yonghui Zhang (279832)

“…In this work, we modified Non-dominated Sorting Genetic Algorithm with the core algorithm of PEST (MNSGA-II) and compared it to two other algorithms of Generalized Likelihood Uncertainty Estimation (GLUE) and Differential Evolution (DE) to calibrate the cultivar-specific parameters (CSPs) of CROPGRO-Soybean phenological model (CSPM) so as to exactly simulate the soybean phenology using the multi-source datasets of multi-site, multi-year, and multi-cultivar. …”

Multi-step ahead prediction plots for each model. by Yaopeng Han (22622718)

“…The model’s performance is validated through ablation experiments and comparisons of single-step and multi-step predictions with recent benchmark models. …”

Schematic illustration of the multi-type biological network used in APDCA. by Yangsong He (13909371)

Flowchart of informer prediction. by Wenjuan Zhou (115285)

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A machine learning framework enhanced by hybrid optimization for precise solar power generation prediction by Weibin Wang (1968658)

“…Further refinement of the predictive performance of this model has been done by incorporating Tunicate Swarm Algorithm (TSA) and Sooty Tern Optimization Algorithm (STOA). …”

Results of RF algorithm screening factors. by Jintao Li (448681)

Prediction indicators of unit 5 in KDD CUP. by Wenjuan Zhou (115285)

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IoU measures the overlap between predicted bounding boxes and ground truth boxes. by Yang Zhang (30734)

Health assessment process diagram. by Wenjuan Zhou (115285)

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Two-dimensional scatter plot of wind speed, blade deflection angle, and power. by Wenjuan Zhou (115285)

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Prediction indicators for unit 2 of Longyuan wind farm. by Wenjuan Zhou (115285)

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Sample data of wind speed, blade angle, active power, and derivative rate. by Wenjuan Zhou (115285)

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