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All Journal International Journal of Electrical and Computer Engineering
Lyhyaoui, Abdelouahid
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Computer Science & IT Electrical & Electronics Engineering

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Pedestrian level of service for sidewalks in Tangier City Benhadou, Marwane; El Gonnouni, Amina; Lyhyaoui, Abdelouahid
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1048-1057

Abstract

The pedestrian level of service (PLOS) is a measure that quantifies walkway comfort levels. PLOS defined into six categories (A, B, C, D, E, and F) each level defines the range of values, for example, a good level (best traffic condition) is defined with the letter A until reaching the worst level, F (high congestion). This article aims to define the PLOS on sidewalks considering walking conditions in Tangier City (Morocco). Sidewalks are analyzed using video recording in the urban center of Tangier City. The collected data are pedestrian flow and effective sidewalk width. Each level contains a range of values that corresponds to the pedestrian flow that defines the level of service. Clustering techniques are used to identify the threshold of each level using a self-organizing map (SOM). The results are different from those obtained with other methods because pedestrian traffic differs from country to country.
Pedestrian flow prediction in commercial avenue Benhadou, Marwane; Gonnouni, Amina El; Lyhyaoui, Abdelouahid
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5848-5857

Abstract

Mobility plans are one of the most important management tools for city development and an important factor for society and economic growth, where pedestrians are the end goal of any mobility plan. Human behavior is generally unpredictable, and many attempts have been interested at pedestrians' mobility in urban environments, both microscopic and macroscopic (flow, density, and speed) levels. The objective of pedestrian traffic flow prediction is to predict the number of pedestrians at the next moment. Assisting operators and city managers in making decisions in urban environments such as emergency support systems, and quality-of-service evaluation. This study aims to model and predict bi-directional pedestrian flow in a commercial avenue, based on two essential stages, data collection through video recording over two months (pedestrian flow) and data analysis using machine learning algorithms that provide a lower error and a higher accuracy rate. Two metrics were selected as basic measures to evaluate the model performances, root mean square error (RMSE) and coefficient of determination R2. Artificial neural network (ANN) gives a little better performance and fitness.
Validity of a graph-based automatic assessment system for programming assignments: human versus automatic grading Zougari, Soundous; Tanana, Mariam; Lyhyaoui, Abdelouahid
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2867-2875

Abstract

Programming is a very complex and challenging subject to teach and learn. A strategy guaranteed to deliver proven results has been intensive and continual training. However, this strategy holds an extra workload for the teachers with huge numbers of programming assignments to evaluate in a fair and timely manner. Furthermore, under the current COVID-19 distance teaching circumstances, regular assessment is a fundamental feedback mechanism. It ensures that students engage in learning as well as determines the extent to which they reached the expected learning goals, in this new learning reality. In sum, automating the assessment process will be particularly appreciated by the instructors and highly beneficial to the students. The purpose of this paper is to investigate the feasibility of automatic assessment in the context of computer programming courses. Thus, a prototype based on merging static and dynamic analysis was developed. Empirical evaluation of the proposed grading tool within an introductory C-language course has been presented and compared to manually assigned marks. The outcomes of the comparative analysis have shown the reliability of the proposed automatic assessment prototype.
Taxi-out time prediction at Mohammed V Casablanca Airport Zbakh, Douae; El Gonnouni, Amina; Benkacem, Abderrahmane; Said Kasttet, Mohammed; Lyhyaoui, Abdelouahid
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp2126-2134

Abstract

Airports are vital for global connectivity. However, the increasing volume of air travel has presented significant challenges in airport managing. Accurate predictions of taxi-out times (TXOT) offer potential to enhance airport performance, minimize delays, optimize airline schedules, and enhance customer satisfaction. This paper focuses on developing a machine learning model to forecast taxi-out times at Mohammed V Airport. Historical taxiing data from various airports will be analyzed to predict taxi-out times based on diverse runway-stand combinations and congestion levels. we used neural network (NN), support vector machines (SVM), and regression tree (RT) in order to create a real-time model that forecasts TXOT and congestion levels for different runway-stand combinations. The result showed that the NN model outperformed other forecasting models when their performances are compared using the mean absolute percentage error, root mean square error as accuracy measures.
Co-Authors Benhadou, Marwane Benkacem, Abderrahmane El Gonnouni, Amina Gonnouni, Amina El Said Kasttet, Mohammed Tanana, Mariam Zbakh, Douae Zougari, Soundous