Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models by Ayub Mohammadi, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, Nadhir Al-Ansari

“…Flooding is one of the most damaging natural hazards globally. During the past three years, floods have claimed hundreds of lives and millions of dollars of damage in Iran. …”
Get full text

Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat by Yidong Liu, Dali Ding, Mulai Tan, Yuequn Luo, Ning Li, Huan Zhou

“…Compared with decision-making methods based on optimization algorithms and differential games, the win rate is increased by about 17% and 18%, respectively, and the single-step decision-making time is less than 0.02 s, demonstrating high real-time performance and win rate. …”
Get full text

Decision Feedback Equalization-Based Low-Complexity Interference Cancellation and Signal Detection Technique Based for Non-Orthogonal Signaling by Myung-Sun Baek, Hyoung-Kyu Song

Get full text

Induction of Convolutional Decision Trees for Semantic Segmentation of Color Images Using Differential Evolution and Time and Memory Reduction Techniques by Adriana-Laura López-Lobato, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes

Get full text

Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates by Elif Keles, Syed Yaseen Ali, Pia Wintermark, Pieter Annaert, Floris Groenendaal, Suzan Şahin, Mehmet Yekta Öncel, Didem Armangil, Esin Koc, Malcolm R. Battin, Alistair J. Gunn, Adam Frymoyer, Valerie Chock, Djalila Mekahli, John van den Anker, Anne Smits, Karel Allegaert, Ulas Bagci

Get full text

A Developed Mathematical Model for Designing a Multilevel Sustainable Supply Chain Network Taking into Account Environmental Decisions by Mehrab Paydarfard, Roya Pirzadeh, Ali Ahmadi, Masoud Zohrabi, Farkhondeh Mortaz Hejri, Malek Hasan

Get full text

A novel methodological approach to SaaS churn prediction using whale optimization algorithm. by Muhammed Kotan, Ömer Faruk Seymen, Levent Çallı, Sena Kasım, Burcu Çarklı Yavuz, Tijen Över Özçelik

“…The scarcity of research on customer churn models in SaaS, particularly regarding diverse feature selection methods and predictive algorithms, highlights a significant gap. Addressing this would enhance academic discourse and provide essential insights for managerial decision-making. …”
Get full text

Penggunaan Decision Tree dalam Penentuan Faktor yang Mempengaruhi Status Gizi Buruk Balita di Kelurahan Tamamaung by Tithania Indah Permata Hati, Rahman Rahman, Adhy Rizaldy

Get full text

Accurate irrigation decision-making of winter wheat at the filling stage based on UAV hyperspectral inversion of leaf water content by Xuguang Sun, Baoyuan Zhang, Menglei Dai, Cuijiao Jing, Kai Ma, Boyi Tang, Kejiang Li, Hongkai Dang, Limin Gu, Wenchao Zhen, Xiaohe Gu

“…The SPA algorithm also improved the inversion efficiency of LWC. …”
Get full text

A Novel Approach on Decision Support System Based on the Aczel-Alsina Aggregation Operators and Their Applications to Supplier Selection Problems by Yong-Long Wang, Ebenezer Bonyah, Mashael Khayyat, Zubair Ahmad, Muhammad Shakeel, Waris Khan

Get full text

Group decision-making framework using generalized heronian mean operators in quasi rung orthopair fuzzy environment with applications by Muhammad Bilal, Jawad Ali, Muhammad Fawad Tariq, Mohammad Mehedi Hassan

Get full text

A Discretionary Lane-Changing Decision-Making Mechanism Incorporating Drivers’ Heterogeneity: A Signalling Game-Based Approach by Haipeng Shao, Miaoran Zhang, Tao Feng, Yifan Dong

Get full text

Cutoff Grade Optimization on Operative Decision Variables with Geological Uncertainty in an Underground Gold Mine: A Real Case Study by Diego Alejandro Toro Morales, Giovanni Franco Sepúlveda, Erick de la Barra, Juan Camilo Del Río Cuervo

Get full text

Method for decomposition a global task into local tasks through the process of collective decision making in swarm robotic systems by V. I. Petrenko, F. B. Tebueva, V. O. Antonov, S. S. Ryabtsev, A. S. Pavlov

Get full text

A Decision Support System for Classifying Suppliers Based on Machine Learning Techniques: A Case Study in the Aeronautics Industry by Ana Claudia Andrade Ferreira, Alexandre Ferreira de Pinho, Matheus Brendon Francisco, Laercio Almeida de Siqueira, Guilherme Augusto Vilas Boas Vasconcelos

Get full text

A Decentralized Partially Observable Markov Decision Model with Action Duration for Goal Recognition in Real Time Strategy Games by Peng Jiao, Kai Xu, Shiguang Yue, Xiangyu Wei, Lin Sun

Get full text

Model-Based RL Decision-Making for UAVs Operating in GNSS-Denied, Degraded Visibility Conditions with Limited Sensor Capabilities by Sebastien Boiteau, Fernando Vanegas, Julian Galvez-Serna, Felipe Gonzalez

Get full text

Blind recognition of primitive BCH code based on average cosine conformity by Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, Yufeng LONG

“…In order to overcome the poor performance of existing algorithms for recognition of BCH code in low signal-to-noise ratio (SNR),a recognition algorithm based on average cosine conformity was proposed.Firstly,by traversing the possible values of code length and m-level primitive polynomial fields,the code length was identified by matching the initial code roots.Secondly,on the premise of recognizing the code length,the GF(2^m) domain was traversed under the m-level primitive polynomial and the primitive polynomial with the strongest error-correcting ability was the generator polynomial for the domain.Finally,the minimum common multiple corresponding to the minimum polynomial of code roots was obtained,and the BCH code generator polynomial was recognized.In checking matching,the statistic of average cosine conformity was introduced.The optimal threshold was solved based on the minimum error decision criterion and distribution of the statistic to realize the fast identification of the BCH.The simulation results show that the deduced statistical characteristics are consistent with the actual situation,and the proposed algorithm can achieve reliable recognition under SNR of 5 dB and code length of 511.Comparing with existing algorithms,the performance of the proposed algorithm is better than that of the existing soft-decision algorithm and 1~3.5 dB better than that of the hard-decision algorithms.…”
Get full text

Blind recognition of primitive BCH code based on average cosine conformity by Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, Yufeng LONG

“…In order to overcome the poor performance of existing algorithms for recognition of BCH code in low signal-to-noise ratio (SNR),a recognition algorithm based on average cosine conformity was proposed.Firstly,by traversing the possible values of code length and m-level primitive polynomial fields,the code length was identified by matching the initial code roots.Secondly,on the premise of recognizing the code length,the GF(2^m) domain was traversed under the m-level primitive polynomial and the primitive polynomial with the strongest error-correcting ability was the generator polynomial for the domain.Finally,the minimum common multiple corresponding to the minimum polynomial of code roots was obtained,and the BCH code generator polynomial was recognized.In checking matching,the statistic of average cosine conformity was introduced.The optimal threshold was solved based on the minimum error decision criterion and distribution of the statistic to realize the fast identification of the BCH.The simulation results show that the deduced statistical characteristics are consistent with the actual situation,and the proposed algorithm can achieve reliable recognition under SNR of 5 dB and code length of 511.Comparing with existing algorithms,the performance of the proposed algorithm is better than that of the existing soft-decision algorithm and 1~3.5 dB better than that of the hard-decision algorithms.…”
Get full text

Detecting Student Engagement in an Online Learning Environment Using a Machine Learning Algorithm by Youssra Bellarhmouch, Hajar Majjate, Adil Jeghal, Hamid Tairi, Nadia Benjelloun

“…We utilized supervised machine learning algorithms to forecast engagement at three levels: quizzes, exams, and lessons, drawing from a Kaggle database. …”
Get full text