Depth-first-search-tree based D2D power allocation algorithms for V2I/V2V shared 5G network resources

Hussein, Hanan; Radwan, Mohamed Hanafy; El-Sayed, Hesham; El-Kader, Sherine M. Abd

doi:10.1007/s11276-021-02649-4

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…The rollout of fifth-generation networks (5G) provides a unique opportunity for creating and exploiting innovative solutions to improve communication between all transport system components and reduce road crash casualties. The application of 5G in traffic environments could be a game changer over the next years as it enhances direct communication capabilities with very low latency such as Vehicle-to-Vehicle (V2V), Vehicleto-Infrastructure (V2I) and Vehicle-to-Everything (V2X) [95]. This framework could assist in the collection of a wealth of real-time data that can be also used for the extraction of various SSMs that could be integrated into traditional road safety analysis.…”

Section: Future Research Directionsmentioning

confidence: 99%

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

2023

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Historical road crash data are the main indicator for measuring road safety outcomes. Over the past few decades, significant efforts have been made in obtaining and exploiting Surrogate Safety Measures (SSMs). SSMs have the potential to provide excellent sustainable road safety indicators and proxy measurements which can complement traditional historical crash analyses or even substitute them. By using SSMs, crash data collection demands can be bypassed and areas can be investigated before crashes occur. Due to such advantages, the objective of the present research is to provide a review of the scientific literature regarding studies exploiting SSMs for historical crash record investigations. Specifically, 34 studies were examined, providing insights on the different types of SSMs collected under real road environment conditions, the way they are collected, their connection with specific road crash types, and the type of the developed statistical models are examined and discussed. Particular focus is also placed on the temporal dimension of the collection period of both SSMs and road crashes. Finally, the overall trends deriving from the reviewed studies are summarized and future research directions are provided.

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Section: Future Research Directionsmentioning

confidence: 99%

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

2023

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“…By guaranteeing a lower bound on V2I ergodic capacity, OPT-DFST algorithm shows better network bandwidth with effective runtime than other algorithms. It is also capable of operating even at an increased number of V2V per channel [19].…”

Section: Introductionmentioning

confidence: 99%

Application of an Expert System with the Breadth First Search (BFS) Method in Diagnosing Areca Plant Diseases

Pane,

Rianti,

Marfalino

2024

jcsitech

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Current technological developments are growing very quickly and have produced a lot of software or systems that can make things easier for humans. Continuous scientific progress drives extensive technological development. One form of information technology known is an information system. One popular type of information system is an expert system, which can be used to improve various services. An expert system is a program that combines human knowledge into a computer to help solve problems that are usually solved by experts. This research aims to identify gaps in research that has been conducted, as well as encourage the development of new ideas and increase capabilities in utilizing existing research resources. Areca nut is a high agricultural resource so it has many benefits in the pharmaceutical industry. . The method that will be used in this research is Breadth First Search (BFS). The algorithm carries out the search process on all nodes that are at the same level or hierarchy one by one. An algorithm that performs a wide search that visits nodes in preorder, that is, visits a node first. There are 16 data on areca plant diseases here and have 33 symptoms which will be processed using the Breadth First Search Method. By diagnosing areca plant diseases using an expert system, it is hoped that we can find more in-depth information about diseases in areca palm trees.

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“…Due to the large number of vehicles and complex transport networks, the data are characterized by large size, high variation, and high dynamics. In particular, the recent development of smart cities 3 lead to more and more sensors that are installed on vehicles, enabling the communication between vehicles and peripheral equipment at any time, such as vehicle to vehicle (V2V) 4 communication, vehicle to infrastructure (V2I) 5 communication, and vehicle to everything (V2X) information exchangesHence, vehicles can send their position information at any time. This Internet of Vehicles technology is applied based on integrating technologies such as GPS navigation, 6,7 and mass of traffic flow data are generated 8 .…”

Section: Introductionmentioning

confidence: 99%

Short‐term traffic flow prediction based on whale optimization algorithm optimized BiLSTM_Attention

Liu

Zhao

et al. 2022

Concurrency and Computation

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With the growths in population and vehicles, traffic flow becomes more complex and uncertain disruptions occur more often. Accurate prediction of urban traffic flow is important for intelligent decision-making and warning, however, remains a challenge. Many researchers have applied neural network methods, such as convolutional neural networks and recurrent neural networks, for traffic flow prediction modeling, but training the conventional network that can obtain the best network parameters and structure is difficult, different hyperparameters lead to different network structures. Therefore, this article proposes a traffic flow prediction model based on the whale optimization algorithm (WOA) optimized BiLSTM_Attention structure to solve this problem. The traffic flow is predicted first using the BiLSTM_Attention network which is then optimized by using the WOA to obtain its four best parameters, including the learning rate, the training times, and the numbers of the nodes of two hidden layers. Finally, the four best parameters are used to build a WOA_BiLSTM_Attention model. The proposed model is compared with both conventional neural network model and neural network model optimized by the WOA. Based on the evaluation metrics of MAPE, RMSE, MAE, and R2, the WOA_BiLSTM_Attention model proposed in this article presents the best performance.

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Depth-first-search-tree based D2D power allocation algorithms for V2I/V2V shared 5G network resources

Cited by 6 publications

References 17 publications

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

Application of an Expert System with the Breadth First Search (BFS) Method in Diagnosing Areca Plant Diseases

Short‐term traffic flow prediction based on whale optimization algorithm optimized BiLSTM_Attention

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