scholarly journals ANALISIS KINERJA DAN PENGEMBANGAN PELABUHAN LAUT DI BALI (STUDI KASUS: PELABUHAN CELUKAN BAWANG)

1970 ◽  
Vol 4 (1) ◽  
Author(s):  
Kadek Arisena Wikarma ◽  
I W Suweda ◽  
I G. Putu Suparsa
Keyword(s):  
Traffic Flow ◽  
Financial Analysis ◽  
Linear Regression Analysis ◽  
Poor Performance ◽  
Multiple Linear Regression Analysis ◽  
Development Plan ◽  
Traffic Flows ◽  
Port Development ◽  
Traffic Flow Prediction ◽  
Standard Value

Abstract: Celukan Bawang Harbour is located in the northern province of Bali. Port traffic through the Celukan Bawang Harbour during the period of 2005-2009 has decreased. So It is necessary for the performance evaluation of the port so that the reduction in traffic flows of goods can be determined. In addition, this study also predict traffic flow of goods 30 years future so it can be evaluated development of the port in the future . The evaluation was done based on the performance data Celukan Bawang Harbour last 10 years. Then a prediction of traffic flows to goods the next 30 years using multiple linear regression analysis. For the evaluation of the development of the port to analyze the financial feasibility of the port master development plan (RPIP) 10 years  from 2014 to 2023 years that compare to the development plan based on a prediction of traffic flows. Based on the evaluation of operating performance, port obtained poor performance. This is evident from the performance indicators in 2013 that the waiting time: 58 hours and BOR value: 88 % above the standard value is specified, while the percentage of effective time / Berthing time: 31.6%, SOR: 6%, Yor: 0% is far below the standard set value. Meanwhile, if the predicted assuming port performance has been improved, the traffic flow of goods grew 10.90% annually. Financial analysis based RPIP port development is not feasible to get the value NPV = -1,521,941,710 BCR value = 0.9828 and a IRR = 11.46%, while the development of port based traffic flow prediction goods with the sensitivity condition cost increase 15% and benefits decrease 15% get decent results with NPV = 12,191,952,255 and BCR value = 1.4546.

TripRes

2021 ◽  
Vol 17 (2) ◽  
pp. 1-21
Author(s):  
Xiaolong Xu ◽  
Zijie Fang ◽  
Lianyong Qi ◽  
Xuyun Zhang ◽  
Qiang He ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Discrete Distribution ◽  
Resource Provisioning ◽  
Path Selection ◽  
Urban Traffic ◽  
Traffic Flows ◽  
Multimedia Services ◽  
Traffic Flow Prediction ◽  
The City ◽  
Multimedia Surveillance

The Internet of Vehicles (IoV) connects vehicles, roadside units (RSUs) and other intelligent objects, enabling data sharing among them, thereby improving the efficiency of urban traffic and safety. Currently, collections of multimedia content, generated by multimedia surveillance equipment, vehicles, and so on, are transmitted to edge servers for implementation, because edge computing is a formidable paradigm for accommodating multimedia services with low-latency resource provisioning. However, the uneven or discrete distribution of the traffic flow covered by edge servers negatively affects the service performance (e.g., overload and underload) of edge servers in multimedia IoV systems. Therefore, how to accurately schedule and dynamically reserve proper numbers of resources for multimedia services in edge servers is still challenging. To address this challenge, a traffic flow prediction driven resource reservation method, called TripRes, is developed in this article. Specifically, the city map is divided into different regions, and the edge servers in a region are treated as a “big edge server” to simplify the complex distribution of edge servers. Then, future traffic flows are predicted using the deep spatiotemporal residual network (ST-ResNet), and future traffic flows are used to estimate the amount of multimedia services each region needs to offload to the edge servers. With the number of services to be offloaded in each region, their offloading destinations are determined through latency-sensitive transmission path selection. Finally, the performance of TripRes is evaluated using real-world big data with over 100M multimedia surveillance records from RSUs in Nanjing China.

Optimization driven cellular automata for traffic flow prediction at signalized intersections

2021 ◽  
Vol 40 (1) ◽  
pp. 1547-1566
Author(s):  
Shuang You ◽  
Yaping Zhou
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Fitness Function ◽  
Traffic Density ◽  
Traffic Flows ◽  
Average Speed ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Ca Model ◽  
Signalised Intersection

The traffic flow prediction using cellular automata (CA) is a trendy research domain that identified the potential of CA in modelling the traffic flow. CA is a technique, which utilizes the basic units for describing the overall behaviour of complicated systems. The CA model poses a benefit for defining the characteristics of traffic flow. This paper proposes a modified CA model to reveal the prediction of traffic flows at the signalised intersection. Based on the CA model, the traffic density and the average speed are computed for studying the characteristics and spatial evolution of traffic flow in signalised intersection. Moreover, a CA model with a self-organizing traffic signal system is devised by proposing a new optimization model for controlling the traffic rules. The Sunflower Cat Optimization (SCO) algorithm is employed for efficiently predicting traffic. The SCO is designed by integrating the Sunflower optimization algorithm (SFO) and Cat swarm optimization (CSO) algorithm. Also, the fitness function is devised, which helps to guide the control rules evaluated by traffic simulation using the CA model. Thus, the cellular automaton is optimized using the SCO algorithm for predicting the traffic flows. The proposed Sunflower Cat Optimization-based cellular automata (SCO-CA) outperformed other methods with minimal travel time, distance, average traffic density, and maximal average speed.

Factors Affecting Traffic Accidents Density on Selected Multilane Rural Highways

2021 ◽  
Vol 7 (7) ◽  
pp. 1183-1202
Author(s):  
Amjad H. Al-Bayati ◽  
Ahmad S. Shakoree ◽  
Zahraa A. Ramadan
Keyword(s):  
Traffic Flow ◽  
Traffic Accidents ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Maximum Speed ◽  
Rural Highways ◽  
Factors Affecting ◽  
Driving Speed ◽  
Wide Range

Estimations of average crash density as a function of traffic elements and characteristics can be used for making good decisions relating to planning, designing, operating, and maintaining roadway networks. This study describes the relationships between total, collision, turnover, and runover accident densities with factors such as hourly traffic flow and average spot speed on multilane rural highways in Iraq. The study is based on data collected from two sources: police stations and traffic surveys. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. Three highways are selected in Wassit governorate as a case study to cover the studied locations of the accidents. The selection includes Kut–Suwera, Kut–ShekhSaad, and Kut–Hay multilane divided highways located in the south of Iraq. The preliminary presentation of the studied highways was performed using Geographic Information System (GIS) software. Data collection was done to obtain crash numbers and types over five years with their locations, hourly traffic flow, and average spot speed and define roadway segments lengths of crash locations. The cumulative speed distribution curves introduce that the spot speed spectrum for each highway's whole traffic extends over a relatively wide range, indicating a maximum speed of 180 kph and a minimum speed of 30 kph. Multiple linear regression analysis is applied to the data using SPSS software to attain the relationships between the dependent variables and the independent variables to identify elements strongly correlated with crash densities. Four regression models are developed which verify good and strong statistical relationships between crash densities with the studied factors. The results show that traffic volume and driving speed have a significant impact on the crash densities. It means that there is a positive correlation between the single factors and crash occurrence. The higher volumes and the faster the driving speed, the more likely it is to crash. As the hourly traffic flow of automobile grows, the need for safe traffic facilities also extended. Doi: 10.28991/cej-2021-03091719 Full Text: PDF

Synchronized Entry-Traffic Flow Prediction for Regional Expressway System Based on Multidimensional Tensor

2021 ◽  
pp. 036119812110111
Author(s):  
Hong Gao ◽  
Zengjie Wang ◽  
Zhenjun Yan ◽  
Zhaoyuan Yu ◽  
Wen Luo ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Moving Average ◽  
Three Dimensional ◽  
Prediction Method ◽  
Tensor Decomposition ◽  
New Method ◽  
Traffic Flows ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Spatial Locations

Predicting entry-traffic flows synchronously could enable inferences about the changing trends and spatial structure of dynamic traffic flows in an expressway network. This research develops a synchronized entry-traffic flow prediction method for regional expressway systems. The new method first organizes numerous entry-traffic flows as a three-dimensional (time slots, spatial locations, and vehicle types) tensor, then applies tensor decomposition to extract their temporally changing features. After forecasting the temporally changing features, predicted values of entry-traffic flows can be calculated synchronously by tensor reconstruction. Data from hourly entry-traffic flows involving nine vehicle types and 201 spatial locations in a regional expressway system of China are used to discuss the performance of this new method. The results show that the new method could obtain prediction results with high overall accuracy. Comparative experiments indicate that the new method and existing methods (autoregressive integrated moving average, or ARIMA, and Holt-Winters) could generate prediction results with similar accuracy. However, the proposed method has the advantage of reducing the number of time series that need to be handled in the prediction of numerous entry-traffic flows for regional expressway systems. This method might be helpful for administrators to guide and manage vehicles so that they enter the expressway system effectively.

Highway Short-Term Traffic Flow Prediction with Traffic Flows from Multi Entry Stations

2020 ◽  
Author(s):  
Housong Ruan ◽  
BangYu Wu ◽  
Bin Li ◽  
Zhu Chen ◽  
Han Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Flows ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction

Associations Between Physical and Executive Functions Among Community-Dwelling Older Men and Women

2021 ◽  
pp. 1-8
Author(s):  
Anna Tirkkonen ◽  
Jenni Kulmala ◽  
Tuomo Hänninen ◽  
Timo Törmäkangas ◽  
Anna Stigsdotter Neely ◽  
...  
Keyword(s):  
Older Adults ◽  
Executive Functions ◽  
Cognitive Functions ◽  
Linear Regression Analysis ◽  
Poor Performance ◽  
Multiple Linear Regression Analysis ◽  
Community Dwelling ◽  
Men And Women ◽  
Age Related ◽  
Physical Functions

Walking is a complex task requiring the interplay of neuromuscular, sensory, and cognitive functions. Owing to the age-related decline in cognitive and physical functions, walking may be compromised in older adults, for cognitive functions, especially poor performance in executive functions, is associated with slow walking speed. Hence, the aim of this study was to investigate the associations between different subdomains of executive functions and physical functions and whether the associations found differ between men and women. Multiple linear regression analysis was performed on data collected from 314 community-dwelling older adults who did not meet physical activity guidelines but had intact cognition. Our results showed that, while executive functions were associated with gait and lower extremity functioning, the associations depended partly on the executive process measured and the nature of the physical task. Moreover, the associations did not differ between the sexes.

scholarly journals The Effects of Speed and Flow Characteristics on Crash Rates for Wasit Multi-lane Highways in Iraq

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Amjad H. Albayati ◽  
Zahraa A. Ramadan
Keyword(s):  
Traffic Flow ◽  
Linear Regression Analysis ◽  
Flow Characteristics ◽  
Multiple Linear Regression Analysis ◽  
Strongly Correlated ◽  
Rural Highways ◽  
Traffic Crash ◽  
Crash Rates ◽  
Fatal Crash ◽  
Statistical Relationships

This study describes traffic crash rates in selected multilane rural highways in Wasit governorate in Iraq. The main objective of this research is to investigate relationships between total, fatal crash rates and their kinds and factors such as hourly traffic flow and average spot speed. The study is based on data collected from two sources: police stations and traffic surveys. Three highways are selected to cover the locations of the accidents. The selection includes Kut – Suwera with five segments, Kut – ShekhSaad with three segments, and Kut – Hay with two segments multilane divided highways. Multiple linear regression analysis is applied to the data by using SPSS software to attain the relationships between the dependent variables and the independent variables in order to identify elements that are strongly correlated with crashes rates and severity. Seven regression models are developed which verify weak and strong statistical relationships between crashes types and average spot speed with hourly traffic flow respectively. As the hourly traffic flow of automobile grows, the need for safe traffic facilities also grown.  

scholarly journals EFISIENSI ALOKATIF USAHATANI PADI ORGANIK LAHAN SAWAH DI KABUPATEN BANYUMAS

2019 ◽  
Vol 12 (3) ◽  
pp. 1
Author(s):  
Kusmantoro Edy Sularso ◽  
Agus Sutanto ◽  
Basuki Iman Cahyono ◽  
Niken Hapsari Arimurti
Keyword(s):  
Financial Analysis ◽  
Organic Fertilizer ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Survey Method ◽  
Rice Farming ◽  
Rice Farmers ◽  
Organic Rice ◽  
Census Number ◽  
Input Prices

Organic rice farming actually has long been known by rice farmers in Banyumas Regency. Most rice farmers in general are still reluctant to grow organic rice. Most of them still plant non-organic rice, with consideration that they are used to it, the input is easily accessed and obtained, the sales and marketing are easy. Unless there are psychological constraints experienced by farmers there is a concern that using organic fertilizer productivity per land area will decrease, because non-organic rice farmers are accustomed to using inorganic fertilizers who are well aware of the predictions of fertilizer use related to productivity. The research objectives are to 1) determine the role of organic fertilizer on the productivity of organic rice farming; 2) the effect of output prices and input prices on the efficient use of inputs. The research method used was the survey method, the method of determining respondents using a census (number of farmers 39 people). The analytical method uses the financial analysis method, multiple linear regression analysis (Cobb Douglas production function). The results showed that throughout Banyumas District there were only 39 farmers who carried out organic rice farming. Financially, organic rice farming in Banyumas Regency is profitable, with an average profit of Rp.6,698,917, -, with the record that family labor is included as the cost and land is calculated as rent. The addition of seeds, manure, liquid organic fertilizer (POC), organic KCl fertilizer can increase the productivity of organic rice in a row 0.5539%, 0.5339%, 0.1893% and 0.1179% from each additional input of 1%. Addition of pesticides will reduce productivity by 0.1725% from the addition of these inputs by 1%. The effect of output prices and input prices on the efficient use of seed inputs, has been efficient, while the use of manure, and organic KCl and POC have not been efficient and the use of pesticides is inefficient  Keyword : efficient, financial, organic, productivity, liquid organic fertilizer

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