scholarly journals A Study of Spatiotemporal Distribution of Mobility-On-Demand in Generating Pick-Up/Drop-Offs Location Placement

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 746-766
Author(s):  
Ryan K. Gunawan ◽  
Susilawati Susilawati
Keyword(s):  
Genetic Algorithm ◽  
Spatial Distribution ◽  
Spatiotemporal Distribution ◽  
Walking Distance ◽  
Clustering Method ◽  
Location Optimization ◽  
Demand Distribution ◽  
On Demand ◽  
Time Periods ◽  
The Difference

The location placement of pick-up/drop-offs of ride hailing usually only considers spatial distribution within a certain area. Previous studies often mapped out the potential hotspots for pick-up/drop-offs, benefitting the ride-hailing company and not considering the passengers. Therefore, in this study, we incorporated the spatiotemporal distribution of mobility-on-demand on generating pick-up/drop-off location placement using a genetic algorithm considering the walking distance and minimum demand data served within the radius. The data collected are analyzed through the clustering method, and the resulting cluster centers are fed into the location optimization algorithm. The genetic algorithm is used to optimize the location placement with the consideration of the user’s walking distance and demand. The algorithm is able to find an appropriate placement and determine reliable pick-up/drop-off stations within the study area based on observed spatiotemporal demand despite the difference in demand distribution through different time periods.

scholarly journals Optimasi Cluster Pada Fuzzy C-Means Menggunakan Algoritma Genetika Untuk Menentukan Nilai Akhir

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Putri Elfa Mas`udia ◽  
Retantyo Wardoyo
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Cluster Center ◽  
Local Optimum ◽  
Membership Degree ◽  
Clustering Method ◽  
Final Grade ◽  
Fuzzy C Means ◽  
Group A ◽  
The Difference

AbstrakNilai akhir mahasiswa dapat ditentukan dengan berbagai cara, beberapa diantaranya menggunakan range nilai, standart deviasi, dll. Dalam penelitian ini akan ditawarkan sebuah metode baru untuk menentukan nilai akhir mahasiswa menggunakan clustering dalam hal ini adalah Fuzzy C-Means.Fuzzy C-Means digunakan untuk mengelompokkan sejumlah data dalam beberapa cluster. Tiap data memiliki derajat keanggotaan pada masing-masing cluster antara 0-1 yang diukur melalui fungsi objektif. Pada Fuzzy C-Means ini fungsi objektif diminimumkan menggunakan iterasi yang biasanya terjebak dalam optimum lokal. Algoritma genetika diharapkan dapat menangani masalah tersebut karena algoritma genetika berbasis evolusi yaitu dapat mencari individu terbaik melalui operasi genetika (seleksi, crossover, mutasi) dan dievaluasi berdasarkan nilai fitness. Penelitian ini bertujuan untuk mengoptimasi titik pusat cluster pada Fuzzy C-Means menggunakan algoritma genetika. Hasilnya, bahwa dengan menggunakan GFS didapatkan fungsi objektif yang lebih kecil daripada menggunakan FCM, walaupun membutuhkan waktu yang relative besar. Meskipun selisih antara FCM dan GFS tidak terlalu besar namun hal tersebut berpengaruh pada anggota cluster  Kata kunci— clustering, Fuzzy C-Means, algoritma genetika AbstractThe final grade of students could be determined in various ways, some of which use a range of values, deviation standard, etc. In this study will be offered a new method for determining final grades of students by using the clustering method. In this research the clustering method that will be used is the Fuzzy C-Means (FCM).Fuzzy C-Means is used to group a number of data in multiple clusters. Each data has a degree of membership (the range value of membership degree is 0-1). Membership degree is measured through the objective function. In Fuzzy C-Means,  objective function is minimized by using iteration and is usually trapped in a local optimum. Genetic algorithm is expected to handle these problems. The operation of genetic algorithm based on evolution that is able to find the best individuals through genetic operations (selection, crossover and mutation) and evaluated based on fitness values.This research aims to optimize the cluster center point of FCM by using genetic algorithms. The result of this research shows that by combining the Genetic Algorithm with FCM could obtained a smaller objective function than using FCM, although it takes longer in execution time. Although the difference of objective function that produced by FCM and FCM-Genetic Algorithm combination is not too big each other, but it takes effect on the cluster members. Keywords— clustering, fuzzy c-means, genetic algorithm

Dynamic network intelligent hybrid recommendation algorithm and its application in online shopping platform

2021 ◽  
pp. 1-13
Author(s):  
Yuxuan Gao ◽  
Haiming Liang ◽  
Bingzhen Sun
Keyword(s):  
Online Shopping ◽  
Rapid Development ◽  
Dynamic Network ◽  
Topsis Method ◽  
Recommendation Algorithm ◽  
Time Periods ◽  
The Difference ◽  
Relationship Of ◽  
Hybrid Recommendation ◽  
Novel Model

With the rapid development of e-commerce, whether network intelligent recommendation can attract customers has become a measure of customer retention on online shopping platforms. In the literature about network intelligent recommendation, there are few studies that consider the difference preference of customers in different time periods. This paper proposes the dynamic network intelligent hybrid recommendation algorithm distinguishing time periods (DIHR), it is a integrated novel model combined with the DEMATEL and TOPSIS method to solved the problem of network intelligent recommendation considering time periods. The proposed method makes use of the DEMATEL method for evaluating the preference relationship of customers for indexes of merchandises, and adopt the TOPSIS method combined with intuitionistic fuzzy number (IFN) for assessing and ranking the merchandises according to the indexes. We specifically introduce the calculation steps of the proposed method, and then calculate its application in the online shopping platform.

Closed-Form Correlation of Buildings Energy Use With Key Design Parameters Calibrated Using a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Algorithm ◽  
Closed Form ◽  
Energy Use ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Wide Range ◽  
Variable Function ◽  
Real Coded Genetic Algorithm ◽  
The Difference

This work aims at developing a closed-form correlation between key building design variables and its energy use. The results can be utilized during the initial design stages to assess the different building shapes and designs according to their expected energy use. Prototypical, 20-floor office buildings were used. The relative compactness, footprint area, projection factor, and window-to-wall ratio were changed and the resulting buildings performances were simulated. In total, 729 different office buildings were developed and simulated in order to provide the training cases for optimizing the correlation’s coefficients. Simulations were done using the VisualDOE TM software with a Typical Meteorological Year data file, Kuwait City, Kuwait. A real-coded genetic algorithm (GA) was used to optimize the coefficients of a proposed function that relates the energy use of a building to its four key parameters. The figure of merit was the difference in the ratio of the annual energy use of a building normalized by that of a reference building. The objective was to minimize the difference between the simulated results and the four-variable function trying to predict them. Results show that the real-coded GA was able to come up with a function that estimates the thermal performance of a proposed design with an accuracy of around 96%, based on the number of buildings tested. The goodness of fit, roughly represented by R2, ranged from 0.950 to 0.994. In terms of the effects of the various parameters, the area was found to have the smallest role among the design parameters. It was also found that the accuracy of the function suffers the most when high window-to-wall ratios are combined with low projection factors. In such cases, the energy use develops a potential optimum compactness. The proposed function (and methodology) will be a great tool for designers to inexpensively explore a wide range of alternatives and assess them in terms of their energy use efficiency. It will also be of great use to municipality officials and building codes authors.

scholarly journals Asymmetric correlation of sovereign bond yield dynamics in the Eurozone

2013 ◽  
Vol 60 (6) ◽  
pp. 775-789 ◽  
Author(s):  
Silvo Dajcman
Keyword(s):  
New York ◽  
Debt Crisis ◽  
Bond Markets ◽  
Lower Tail ◽  
Sovereign Bond ◽  
Bond Yield ◽  
Time Periods ◽  
The Difference ◽  
Asymmetric Correlation ◽  
Sovereign Bond Markets

This paper examines the symmetry of correlation of sovereign bond yield dynamics between eight Eurozone countries (Austria, Belgium, France, Germany, Ireland, Italy, Portugal, and Spain) in the period from January 3, 2000 to August 31, 2011. Asymmetry of correlation is investigated pair-wise by applying the test of Yongmiao Hong, Jun Tu, and Guofu Zhou (2007). Whereas the test of Hong, Tu, and Zhou (2007) is static, the present paper provides also a dynamic version of the test and identifies time periods when the correlation of Eurozone sovereign bond yield dynamics became asymmetric. We identified seven pairs of sovereign bond markets for which the null hypothesis of symmetry in correlation of sovereign bond yield dynamics can be rejected. Calculating rolling-window exceedance correlation, we found that the time-varying upper- (i.e. for positive yield changes) and lower-tail correlations (i.e. for negative yield changes) for pair-wise observed sovereign bond markets normally follow each other closely, yet during some time periods (for most pair-wise observed countries, these periods are around the September 11 attack on the New York City WTC and around the start of the Greek debt crisis) the difference in correlation does increase. The results show that the upper- and lower-tail correlation was symmetric before the Eurozone debt crisis for most of the pair-wise observed sovereign bond markets but has become much less symmetric since then.

scholarly journals Determination of Multilayer Soil Strength Parameters Using Genetic Algorithm

2018 ◽  
Vol 4 (10) ◽  
pp. 2383 ◽  
Author(s):  
Seyyed Mohammad Hashemi ◽  
Iraj Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Lateral Displacement ◽  
Error Function ◽  
Back Analysis ◽  
Soil Strength ◽  
Strength Parameters ◽  
Analysis Process ◽  
Project Monitoring ◽  
The Difference ◽  
Python Programming

This paper employs a back analysis method to determine soil strength parameters of the Mohr-Coulomb model from in situ geotechnical measurements. The lateral displacement of a soil nailed wall retaining an excavation in Tehran city used as a criterion for the back analysis. For this purpose, a genetic algorithm is applied as an optimization algorithm to minimize the error function, which can perform the back analysis process. When the accuracy of modeling is verified, the back analysis is performed automatically by creating a link between genetic algorithm in MATLAB and Abaqus software using Python programming language. This paper demonstrated that the genetic algorithm is a particularly suitable tool to determine 9 soil strength parameters simultaneously for 3 soil layers of the project site to decrease the difference of lateral displacement between the results of project monitoring and numerical analysis. The soil strength parameters have increased, with the most changes in Young's modulus of the first to third layers as the most effective parameter, 49.45%, 61.67% and 64.35% respectively. The results can be used in advanced engineering analyses and professional works.

scholarly journals Top-down estimation of carbon monoxide emissions from the Mexico Megacity based on FTIR measurements from ground and space

2012 ◽  
Vol 12 (11) ◽  
pp. 29915-29965 ◽  
Author(s):  
W. Stremme ◽  
M. Grutter ◽  
C. Rivera ◽  
A. Bezanilla ◽  
A. R. Garcia ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Spatial Distribution ◽  
Mexico City ◽  
Emission Flux ◽  
Top Down ◽  
Solar Absorption ◽  
Surface Emission ◽  
The Difference ◽  
Anthropogenic Pollutant ◽  
Total Column

Abstract. Continuous carbon monoxide (CO) total column densities above the UNAM campus in Mexico City have been derived from solar absorption infrared spectroscopic measurements since October 2007. Its diurnal evolution is used in the present study in conjunction with other ground-based and satellite data to develop a top-down emission estimate of the annual CO emission of the Mexico City Metropolitan Area (MCMA). The growth-rate of the total column around noon under low ventilation conditions is calculated and allows us to derive the average surface emission-flux at UNAM, while similar measurements taken at the edge of the MCMA in Tecámac provides information on background CO levels in the Mexico basin. Based on 3 yr of measurements, CO column measurements from the IASI satellite instrument are used to reconstruct the spatial distribution of this anthropogenic pollutant over the MCMA. The agreement between the measured columns of the satellite and ground-based measurements is excellent, particularly when a comparison strategy based on time-displaced air masses is used. The annual emission of the Mexico Megacity is estimated to be (2.15 ± 0.5) Tg yr−1 for the year 2008, while the official inventory for that year reported 1.6 Tg yr−1. The difference is slightly higher than the conservative uncertainty estimated in this work suggesting that the emission might be underestimated by the conventional bottom-up method. A larger discrepancy is found in the spatial distribution of the emissions, when comparing the emission flux over UNAM (derived from the ground-based measurement) with that of the inventory integrated over a representative area. The methodology presented here represents a new and useful strategy to evaluate the contribution of megacities to the global anthropogenic gas emissions. Additionally, three different strategies to compare ground and space-based measurements above an inhomogeneous and strongly contaminated area like Mexico City are presented and discussed.

scholarly journals Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Ahmed H. Aburawwash ◽  
Moustafa Mohammed Eissa ◽  
Azza F. Barakat ◽  
Hossam M. Hafez
Keyword(s):  
Genetic Algorithm ◽  
Accurate Determination ◽  
Probability Of Failure ◽  
System Structure ◽  
Control Element ◽  
Algorithm Optimization ◽  
On Demand ◽  
Uncertainty Sources ◽  
Iec 61508 ◽  
Proposed Model

A more accurate determination for the Probability of Failure on Demand (PFD) of the Safety Instrumented System (SIS) contributes to more SIS realiability, thereby ensuring more safety and lower cost. IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas. However, these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources, which, including high redundant systems architectures, cannot be assessed, have perfect proof test assumption, and are neglegted in partial stroke testing (PST) of impact on the system PFD. On the other hand, determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time. This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem. A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor (DC) and common cause failures (CCF). In order to simulate the proof test effectiveness, the Proof Test Coverage (PTC) factor has been incorporated into the formula. Additionally, the system PFD value has been improved by incorporating PST for the final control element into the formula. The new developed formula is modelled using the Genetic Algorithm (GA) artificial technique. The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables. The proposed model has been applicated on SIS design for crude oil test separator using MATLAB. The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality. Furthermore, the cost and associated implementation testing activities are reduced.

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