Application of Ant Colony Optimization (ACO) Algorithm to Optimize Trans Banyumas Bus Routes

Armond, Abira Massi; Prasetyo, Yogo Dwi; Ediningrum, Wahyurini

doi:10.1109/cyberneticscom55287.2022.9865394

Cited by 3 publications

(5 citation statements)

References 19 publications

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“…The deep belief network is employed to extract the feature mation in the data. Then, the extracted feature information is used as an input of the The ant colony optimization (ACO) algorithm [13] is employed to automatically sel optimal parameter of the SVR, and apply it to the soft measurement model. The fina is to predict the tail diameter based on the DBN-ACO-SVR model, compare the pre The crystal diameter signal used for the data fusion was acquired using a Microvision MV-300UC Camera.…”

Section: Overall Architecture Of the Proposed Methodsmentioning

confidence: 99%

“…Then, the extracted feature information is used as an input of the SVR. The ant colony optimization (ACO) algorithm [13] is employed to automatically select the optimal parameter of the SVR, and apply it to the soft measurement model. The final stage is to predict the tail diameter based on the DBN-ACO-SVR model, compare the predicted results with those of other methods, and validate the data of different lots based on this model.…”

Section: Overall Architecture Of the Proposed Methodsmentioning

confidence: 99%

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A Soft Measurement Method for the Tail Diameter in the Growing Process of Czochralski Silicon Single Crystals

Jiang,

Teng,

Zhao

2024

Applied Sciences

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In the Czochralski silicon single crystal growth process, the tail diameter is a key parameter that cannot be directly measured. In this paper, we propose a real-time soft measurement method that combines a deep belief network (DBN) and a support vector regression (SVR) network based on system identification to accurately predict the crystal diameter. The main steps of the proposed method are as follows: First, we address the delay problem of the effects of the temperature and crystal pulling speed on the tail diameter growth by using a back propagation (BP) neural network based on the mean impact value (MIV) method to determine the optimal delay time. Second, we construct a prediction model of the tail diameter by using the DBN network with the temperature and crystal pulling speed as input variables in the crystal growth process. Third, we improve the DBN network by using the SVR network to enhance its linear regression capability. We also employ the ant colony optimization (ACO) algorithm to obtain the optimal parameters of the SVR network. Finally, we compare the performance of the DBN-ACO-SVR network based on system identification with the DBN and SVR networks, and the results show that our method can effectively deal with the delay problem and achieve the accurate prediction of the tail diameter in the Czochralski silicon single crystal growth process.

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Section: Overall Architecture Of the Proposed Methodsmentioning

confidence: 99%

Section: Overall Architecture Of the Proposed Methodsmentioning

confidence: 99%

A Soft Measurement Method for the Tail Diameter in the Growing Process of Czochralski Silicon Single Crystals

Jiang,

Teng,

Zhao

2024

Applied Sciences

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“…In the following section, the air quality measurement was performed using designated end nodes, and the LoRa network was harnessed to transmit all recorded data to a server for centralized data collection. Equipped with AQI (Air Quality Index) sensors [36], these end nodes were strategically placed in three distinct zones within the city to facilitate the analysis and identification of varying pollution levels arising from factors such as heavy traffic, as well as different environmental conditions like fires, smoke, and dust resulting from construction activities, among others.…”

Section: Measurements In Urban Areamentioning

confidence: 99%

“…In order to determine a viable route, it is essential to incorporate a route selection algorithm [36], which, in this case, will use the pollution data as input to identify the route with the lowest pollution levels. The algorithms and techniques for computing optimal trajectories [37] have already been established and will not be the primary focus of this paper.…”

Section: Usage Of the Air Pollution Mapmentioning

confidence: 99%

Long-Range Network of Air Quality Index Sensors in an Urban Area

Dobra,

Dobra

et al. 2023

Sensors

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In recent times the escalating pollution within densely populated metropolitan areas has emerged as a significant and pressing concern. Authorities are actively grappling with the challenge of devising solutions to promote a cleaner and more environmentally friendly urban landscapes. This paper outlines the potential of establishing a LoRa node network within a densely populated urban environment. Each LoRa node in this network is equipped with an air quality measurement sensor. This interconnected system efficiently transmits all the analyzed data to a gateway, which subsequently sends it to a server or database in real time. These data are then harnessed to create a pollution map for the corresponding area, providing users with the opportunity to assess local pollution levels and their recent variations. Furthermore, this information proves valuable when determining the optimal route between two points in the city, enabling users to select the path with the lowest pollution levels, thus enhancing the overall quality of the urban environment. This advantage contributes to alleviating congestion and reducing excessive pollution often concentrated behind buildings or on adjacent streets.

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“…The rest of this section details the two-brain ML framework within. One brain uses Deep Reinforcement Learning (DRL) to enable UAV fleet autonomy and the other brain uses Ant Colony Optimization (ACO) to enable UAV synchronization and task scheduling [31][32][33].…”

Section: Rssi = (P T + Hmentioning

confidence: 99%

Deployment of an autonomous fleet of UAVs for Assessing the NDVI of Regenerative Farming

Almalki,

Angelides

2023

2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)

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F aris A. Al m al ki 1, M ari os C. A n g eli d es 2 1 D e p art m e nt of C o m p ut er E n gi n e eri n g, C oll e g e of C o m p ut ers a n d I nf or m ati o n T e c h n ol o g y , T aif U ni v ersit y , T aif, S a u di Ar a bi a E m ail: m.f aris @t u. e d u.s a 2 Br u n el D esi g n S c h o ol, C oll e g e of E n gi n e eri n g, D esi g n a n d P h ysi c al S ci e n c es , Br u n el U ni v ersit y L o n d o n , U x bri d g e, U nit e d Ki n g d o m E m ail: m ari os. a n g eli d es @ br u n el. a c. u k

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Application of Ant Colony Optimization (ACO) Algorithm to Optimize Trans Banyumas Bus Routes

Cited by 3 publications

References 19 publications

A Soft Measurement Method for the Tail Diameter in the Growing Process of Czochralski Silicon Single Crystals

A Soft Measurement Method for the Tail Diameter in the Growing Process of Czochralski Silicon Single Crystals

Long-Range Network of Air Quality Index Sensors in an Urban Area

Deployment of an autonomous fleet of UAVs for Assessing the NDVI of Regenerative Farming

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