(2017). Performance evaluation of ANNs and an M5 model tree in Sattarkhan Reservoir inflow prediction. ISH Journal of Hydraulic Engineering. Ahead of Print. doi: 10.1080/09715010.2017.1308277doi:10.1080/09715010.2017.1308277Bahram EsmaeilzadehMohammad Taghi SattariSaeed SamadianfardISH Journal of Hydraulic Engineering
The M5Tree algorithm is utilized for creating a model tree, which runs as follows (Fig. 1). Assume that we have a collection T of training examples. Every case is described by the values of a fixed set of inputs and has a related output value. The point is to build a model that ...
The proposed method, named Deep-m5U, utilizes a hybrid pseudo-K-tuple nucleotide composition (PseKNC) for sequence formulation, a Shapley Additive exPlanations (SHAP) algorithm for discriminant feature selection, and a deep neural network (DNN) as the classifier. Results: The...
2.2.3. M5P-tree model (M5P) M5P-tree is a genetic algorithm learner for regression problems, first introduced by a study [39]. This tree algorithm sets linear regression features on the terminal node and fits into a multivariate linear regression model on each sublocation by classifying or...
forecasting the CS of GPC incorporated with nS. In this case, about 207 tested CS values were collected from literature studies and then analyzed to promote the models. For the first time, eleven effective variables were employed as input model parameters during the modeling process, including ...
3.1. M5P Model Tree Techniques The M5P algorithm, an advanced and efficient technique, is well-suited for analyzing complex systems characterized by a high dimensionality, encompassing a vast number of attributes. Initially introduced by Quinlan [22] as the M5 algorithm, it was designed to addres...
[40] applied the LSSVR model with a gravitational search algorithm for the prediction of wind power. They compared the optimized LSSVR with SVR and NN, and LSSVR's performance was superior to that of the other models. M5RT is not as popular as NF and LSSVR in the field of wind...
# We want to have the same colors for the same cluster from the# MiniBatchKMeans and the KMeans algorithm. Let's pair the cluster centers per# closest one.k_means_cluster_centers = k_means.cluster_centers_order = pairwise_distances_argm...
Stacking is an ensemble ML algorithm that uses meta-learning. The benefit of stacking is that it can harness the capabilities of a range of well-performing models by using their output as input and ultimately achieve a ...
Zhao Mingzhong,Feng Lijie,Wang Jinfeng,et al.Model of Evaluation Production Logistics System of Coal Mine Based On Evidence Theory and Neural Network and Application. 2009 international conference of management science and information system . 2009...