temperature prediction greenhouse multistep
【WALT】predict_and_update_buckets() 与 update_task_pred_demand() 代码详解
@目录【WALT】predict_and_update_buckets() 与 update_task_pred_demand() 代码详解代码展示代码逻辑⑴ 根据 runtime 给出桶的下标⑵ 根据桶的下标预测 pred_demand1. 如果任务刚被创建，直接结束2. 根据下标 bidx 和数 ......
大模型中temperature是什么
Temperature的作用 调节随机性：Temperature控制着模型在生成每个新词时选择可能性的分布。较低的temperature使模型更倾向于选择概率最高的词，而较高的temperature增加了选择较不可能词的概率。 控制创造性：通过调整temperature，我们可以控制生成文本的创造性 ......
Predict potential miRNA-disease associations based on bounded nuclear norm regularization
Predict potential miRNA-disease associations based on bounded nuclear norm regularization 2023/12/8 16:00:57 Predicting potential miRNA-disease associ ......
LandBench 1.0: a benchmark dataset and evaluation metrics for data-driven land surface variables prediction
李老师对于landbench的，基准模型进行的论文。 里面对于变量，数据集的描述，写论文可以用。 题目： “LandBench 1.0: a benchmark dataset and evaluation metrics for data-driven land surface variables ......
Predicting Drug-Target Interactions. drug-target interactions prediction
2023 [j22] Junjun Zhang, Minzhu Xie:Graph regularized non-negative matrix factorization with L2,1 norm regularization terms for drug-target interactio ......
论文精读：STMGCN利用时空多图卷积网络进行移动边缘计算驱动船舶轨迹预测（STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network）
《STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network》 论文链接：https://doi.org/10. ......
论文精读：基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测（Big data driven trajectory prediction based on sparse multi-graph convolutional hybrid network withspatio-temporal awareness）
论文精读：基于具有时空感知的稀疏多图卷积混合网络的大数据驱动船舶轨迹预测 《Big data driven vessel trajectory prediction based on sparse multi-graph convolutional hybrid network with spati ......
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations Shiru Li 1, Minzhu Xie 1, Xi ......
Drug response prediction using graph representation learning and Laplacian feature selection
Drug response prediction using graph representation learning and Laplacian feature selection Minzhu Xie 1 2, Xiaowen Lei 3, Jianchen Zhong 3, Jianxing ......
Predict potential miRNA-disease associations based on bounded nuclear norm regularization
Predict potential miRNA-disease associations based on bounded nuclear norm regularization Yidong Rao 1, Minzhu Xie 1, Hao Wang 1 Affiliations expand P ......
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning Yuchi Chen 1, Minzhu Xie 1, Jie ......
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction Junjun Zhang 1 ......
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm Minzhu Xie 1, Ruijie Xie 2, Hao Wang 3 Affiliations exp ......
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction Junjun ......
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier.
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier. 作者: Lu Cuihong; Xie Minzhu 作者背景: College of Information S ......
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm Minzhu Xie1, Hao Wang1 and Ruijie Xi1 1Hunan Normal ......
Fine-grained Visual Classification with High-temperature Refinement and Background Suppression
摘要 细粒度视觉分类是一项具有挑战性的任务，因为类别之间的相似性很高，单个类别中数据之间的差异不同。为了应对这些挑战，以前的策略侧重于定位类别之间的细微差异并理解其中的判别特征。然而，背景还提供了重要信息，可以告诉模型哪些特征对于分类是不必要的甚至有害，并且过于依赖细微特征的模型可能会忽略全局特征和 ......
论文：Predicting Optical Water Quality Indicators from Remote Sensing Using Machine Learning Algorithms in Tropical Highlands of Ethiopia
水刊，中科院都没有收录。不属于sci。 吃一堑长一智，以后先看属于哪个期刊的。总是忘记。 期刊：Hydrology 浪费时间，啥也没有，没有创新点，就一点点的对比工作量。 “Predicting Optical Water Quality Indicators from Remote Sensing ......
论文：Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network
题目“Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network” (Al Mehedi 等, 2023, ......
论文：Multistep ahead prediction of temperature and humidity in solar greenhouse based on FAM-LSTM model
Multistep ahead prediction of temperature and humidity in solar greenhouse based on FAM-LSTM model 基于 FAM-LSTM 模型的日光温室温湿度多步提前预测 题目：“Multistep ahead pr ......
Precise Temperature Control Solutions
Multi-span Temperature Controllers Provide high-performance multi-span temperature controllers to control temperatures across multiple zones or setpoi ......
Paper Reading: A hybrid deep forest-based method for predicting synergistic drug combinations
为了解决联合用药数据的不平衡、高维、样本数量有限的问题，本文首先构建了一个由药物的物理、化学和生物特性组成的特征集，包括了丰富的生物学信息。特征空间的每个维度都有特定的含义，便于进行可解释性分析，找出预测过程中的关键特征。针对这种不平衡的高维中型数据集，提出了一种改进的基于 Deep Forest ... ......
Linkless Link Prediction via Relational Distillation
目录概符号说明LLP代码 Guo Z., Shiao W., Zhang S., Liu Y., Chawla N. V., Shah N. and Zhao T. Linkless link prediction via relational distillation. ICML, 2023. 概 ......
城市时空预测的统一数据管理和综合性能评估 [实验、分析和基准]《Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis & Benchmark]》
2023年11月1日，还有两个月，2023年就要结束了，希望在结束之前我能有所收获和进步，冲呀，老咸鱼。 摘要 解决了访问和利用不同来源、不同格式存储的不同城市时空数据集，以及确定有效的模型结构和组件。 1.为城市时空大数据设计的统一存储格式“原子文件”，并在40个不同的数据集上验证了其有效性，简化 ......
洛谷P3522/POI2011 TEM-Temperature
涉及知识点：单调队列、贪心、递推 前言 最近找了点单调队列的题练练手，就遇到这道题，本题对于单调队列弹队尾的时候有别于普通单调队列，一些题解并没有写的很清楚，因此写下这篇题解。 题面 Link 你有一个长度为 \(n\) 的序列 \(A\)，告诉你序列中每一个数 \(A_i\) 的取值范围 \(do ......
ST-SSL: 用于交通流量预测的时空自监督学习《Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction》(交通流量预测、自监督)
2023年10月23日，继续论文，好困，想发疯。 论文：Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction Github：https://github.com/Echo-Ji/ST-SSL AAAI 2023的论文 ......
Triangle Graph Interest Network for Click-through Rate Prediction
目录概TGINMotivation: Triangle 的重要性Model代码 Jiang W., Jiao Y., Wang Q., Liang C., Guo L., Zhang Y., Sun Z., Xiong Y. and Zhu Y. Triangle graph interest ne ......
Dual Graph enhanced Embedding Neural Network for CTR Prediction
目录概DG-ENN Guo W., Su R., Tan R., Guo H., Zhang Y., Liu Z., Tang R. and He X. Dual graph enhanced embedding neural network for ctr prediction. KDD, 202 ......
[论文精读][基于点云的蛋白-配体亲和力]A Point Cloud-Based Deep Learning Strategy for Protein-Ligand Binding Affinity Prediction
我需要的信息 代码，论文 不考虑共价键，每个点包括了六种原子信息，包括xyz坐标，范德华半径，原子重量以及来源（1是蛋白质，-1是配体）。原子坐标被标准化，其它参数也被标准化。对不足1024个原子的的复合体，补0到1024。 增加考虑的原子从1024到2048，没有提升，增加原子信息通道，没有提升（ ......
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction
目录概Fi-GNN代码 Li Z., Cui Z., Wu S., Zhang X. and Wang L. Fi-GNN: Modeling feature interactions via graph neural networks for ctr prediction. CIKM, 2019. ......