Mohamed Saleh

Mohamed Saleh
Cairo University | CU · Department of Operations Research and Decision Support (DS)

PhD

About

103
Publications
75,797
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1,101
Citations
Additional affiliations
October 2003 - present
Cairo University
Position
  • Professor

Publications

Publications (103)
Article
Customer Engagement Value (CEV) is a crucial concept for measuring the comprehensive value of a customer without overvaluation or undervaluation. CEV consists of four main components that comprehensively capture the transactional and non-transactional behavior of a customer within a firm. Traditional models contributed to measuring the value of eac...
Article
This work is fulfilled in the context of the optimized monitoring of Internet of Things (IoT) networks. IoT networks are faulty; Things are resource-constrained in terms of energy and computational capabilities; they are also connected via lossy links. For IoT systems performing a critical mission, it is crucial to ensure connectivity, availability...
Article
In the domains of data mining and machine learning, feature selection (FS) is an essential preprocessing step that has a significant effect on the machine learning model’s performance. The primary purpose of FS is to eliminate unnecessary features, resulting in time-space reduction as well as improved the corresponding learning model performance. H...
Article
Full-text available
The study aimed to model and quantify the health burden induced by four non-communicable diseases (NCDs) in Egypt, the first to be conducted in the context of a less developing county. The study used the State-Space model and adopted two Bayesian methods: Particle Filter and Particle Independent Metropolis-Hastings to model and estimate the NCDs’ h...
Article
Purpose The purpose of this paper is to close the gap between the theoretical nature of existing contributions in customer engagement value (CEV) and its need to practically empower business decisions. This is done by proposing a framework that consists of three techniques, each of which combines the components of CEV to make it more comprehensive...
Article
Neutrosophic logic is a very powerful and effective concept. It has different application areas due to its ability to capture the stochasticity in many complex real-life use cases. This paper presents the main types of neutrosophic sets. It also surveys and analyzes its most common applications.
Article
Customer lifetime value (CLV) is an essential measure to determine the level of profitability of a customer to a firm. Customer relationship management treats CLV as the most significant factor for measuring the level of purchases and, consequently, the profitability of a given customer. This motivates researchers to compete in developing models to...
Preprint
Full-text available
The study aimed to model and quantify the health burden induced by four non-communicable diseases in Egypt, the first to be conducted in the context of a less developing county. The study used the State-Space model and adopted two Bayesian methods: Particle Filter and Particle Independent Metropolis-Hastings to model and estimate the NCDs' health b...
Article
Full-text available
In the last decade, data generated from different digital devices has posed a remarkable challenge for data representation and analysis. Because of the high-dimensional datasets and the rapid growth of data volume, a lot of challenges have been encountered in various fields such as data mining and data science. Conventional machine learning classif...
Article
Data clustering is an important unsupervised technique in data mining which aims to extract the natural partitions in a dataset without a priori class information. Unfortunately, every clustering model is very sensitive to the set of randomly initialized centers, since such initial clusters directly influence the formation of final clusters. Thus,...
Article
Data clustering aims to organize data and concisely summarize it according to cluster prototypes. There are different types of data (e.g., ordinal, nominal, binary, continuous), and each has an appropriate similarity measure. However when dealing with mixed data set (i.e., a dataset that contains at least two types of data.), clustering methods use...
Article
Dynamic programming models play a significant role in maximizing customer lifetime value (CLV), in different market types including B2B, B2C, C2B, C2C and B2B2C. This paper highlights the main contributions of applying dynamic programming models in CLV as an effective direct marketing measure. It mainly focuses on Markov Decision Process, Approxima...
Chapter
Full-text available
Customer lifetime value (CLV) is the most reliable indicator in direct marketing for measuring the profitability of the customers. This motivated the researchers to compete in building models to maximize CLV and consequently, enhancing the firm, and the customer relationship. This review paper analyzes the contributions of applying dynamic programm...
Chapter
Planning training sessions is one of the coaches’ main responsibilities in Sports Coaching. Coaches watch their athletes during training, identify key aspects of their performance that can be improved and plan training sessions to address the problems that they have observed. Limited work has been proposed and applied to the generation of training...
Chapter
Critical Infrastructures (CIs) are resources that are essential for the performance of society, including its economy and its security. Large-scale disasters, whether natural or man-made, can have devastating primary (direct) effects on some CI and significant indirect effects (cascading effects) on other CIs, because CIs are interconnected and dep...
Preprint
Full-text available
Dynamic optimization of nonlinear chemical systems -- such as batch reactors -- should be applied online, and the suitable control taken should be according to the current state of the system rather than the current time instant. The recent state of the art methods applies the control based on the current time instant only. This is not suitable for...
Chapter
Full-text available
This paper proposes an enhanced modified Differential Evolution algorithm (MI-EDDE) to solve global constrained optimization problems that consist of mixed/non-linear integer variables. The MI-EDDE algorithm, which is based on the constraints violation, introduces a new mutation rule that sort all individuals ascendingly due to their constraint vio...
Conference Paper
This work developed a system dynamics model to simulate and analyze the future potential state of water resources in Egypt. The developed model illustrates the concept of water resources availability and needs through the use of causal loop diagrams, stock and flow diagrams, equations, and simulation output graphs. This model shows the feedback and...
Article
Full-text available
The performance of Differential Evolution is significantly affected by the mutation scheme, which attracts many researchers to develop and enhance the mutation scheme in DE. In this article, the authors introduce an enhanced DE algorithm (EDDE) that utilizes the information given by good individuals and bad individuals in the population. The new mu...
Preprint
Full-text available
In this paper, we propose an eigenvalue analysis -- of system dynamics models -- based on the Mutual Information concept, which in turn will be estimated via the Kernel Density Estimation concept. We postulate that the Kernel Density Estimation will provide a multivariate sensitivity analysis method that overcomes previous limitations, in addition...
Chapter
Full-text available
Adaptive guided differential evolution algorithm (AGDE) is a DE algorithm that utilizes the information of good and bad vectors in the population, it introduced a novel mutation rule in order to balance effectively the exploration and exploitation tradeoffs. It divided the population into three clusters (best, better and worst) with sizes 100p%, NP...
Article
Full-text available
To ensure robustness in wireless networks, monitoring the network state, performance and functioning of the nodes and links is crucial, especially for critical applications. This paper targets Internet of Things (IoT) networks. In the IoT, devices (things) are vulnerable due to security risks from the Internet. Moreover, they are resource-constrain...
Article
Dynamic pricing is the science of pricing a product in a time-varying way for optimising revenue. There is a slow but steady tendency over the last three decades for major businesses to move from fixed pricing to dynamic pricing. In this paper, we consider the problem of dynamic pricing for wireless broadband data. We propose a novel dynamic pricin...
Article
Full-text available
Dynamic pricing is the science of pricing a product in a time-varying way for optimising revenue. There is a slow but steady tendency over the last three decades for major businesses to move from fixed pricing to dynamic pricing. In this paper, we consider the problem of dynamic pricing for wireless broadband data. We propose a novel dynamic pricin...
Article
Full-text available
Human Activity Recognition has witnessed a significant progress in the last decade. Although a great deal of work in this field goes in recognizing normal human activities, few studies focused on identifying motion in sports. Recognizing human movements in different sports has high impact on understanding the different styles of humans in the play...
Conference Paper
Full-text available
Data clustering aims to organize data and concisely summarize it according to cluster prototypes. There are different types of data (e.g., ordinal, nominal, binary, continuous), and each has an appropriate similarity measure. However when dealing with mixed data set (i.e., a dataset that contains at least two types of data.), clustering methods use...
Conference Paper
Full-text available
Data clustering is an important unsupervised technique in data mining which aims to extract the natural partitions in a dataset without a priori class information. Unfortunately, every clustering model is very sensitive to the set of randomly initialized centers, since such initial clusters directly influence the formation of final clusters. Thus,...
Conference Paper
Full-text available
The emergence of the Internet of Things (IoT) is introducing more and more services and applications such as smart cities. For some services, the availability of elements and the connectivity between them are necessary. The robust functioning of a fragile and often dynamic system in IoT needs strong monitoring which is investigated in this paper. I...
Article
Full-text available
Canonical correlation analysis is a statistical technique that measures the strength of a relationship between many input variables and many output variables. Canonical correlation uses the correlation coefficient, r, as a measure for the strength of the relationship. Unfortunately, this measure suffers from inflation, which occurs when the number...
Conference Paper
Full-text available
This paper is a continuation to our previous work [Yehia, Saleh et al., System Dynamics Conf. (2014)], where we developed a many to one statistical sensitivity analysis method based on the multivariate maximal information coefficient (MMIC). The two main critiques to this method (which we previously developed), were that the complexity of the algor...
Conference Paper
Full-text available
Early warning and intelligent decisions have proved to be important tools to handle the unprecedented events (wildcards) that might emerge in the future. Relying on forecasting techniques only are not enough to shape the future, since they depend only on the historical shape and they generate one image of the future. The Futures Methodologies are c...
Conference Paper
Full-text available
Telecommunications industry is a highly competitive one where operators’ strategies usually rely on significantly reducing minute rate in order to acquire more subscribers and thus have higher market share. However, in the last few years, the numbers of customers are noticeably increasing leading to more stress on the network, and higher congestion...
Conference Paper
Full-text available
In this paper a new time dependent pricing scheme is proposed for revenue management in mobile calls. The pro­ posed scheme considers many essential parameters that affect pricing such as time-of-day seasonality, weekday/weekend sea­ sonality and price demand elasticity for call arrivals and call duration. In this model, each day is partitioned int...
Conference Paper
Full-text available
In this paper we tackle the overbooking problem in hotel revenue management (RM). We propose a simulations­ based approach for the overbooking problem. It is based on accurately estimating all the hotel's processes, such as reservations arrivals, cancelations, length of stay, demand seasonality, etc. Subsequently, all these processes are simulated...
Conference Paper
Full-text available
Public expenditure affects people both directly, through subsidies and transfers, and indirectly through affecting consumption and production activities. The effects of public expenditure depend not only on its absolute values but also on both its composition and the efficiency of this spending. This paper uses data mining techniques to reach a mod...
Conference Paper
Full-text available
This paper proposes a novel statistical sensitivity analysis for dynamic models, which is based on an enhanced maximal information coefficient (MIC) method. We enhanced the MIC method to handle multivariate sensitivity analysis; rather than just univariate analysis. The main motivation of this enhancement is overcoming the research gaps in the curr...
Article
Full-text available
In the last decade, the topic of supply chain performance measurement has attracted the attention of many researchers and practitioners worldwide. A series of significant changes and advancements in the theory and applications has been noticed. Nevertheless, gaps still exist. Current supply chain performance measurement systems still suffer from be...
Article
Full-text available
In long term view, policy/decision makers need to justifiable anticipation for the major future drivers that may effect on their domain key variables. In this paper, we develop a knowledge-based structural analysis approach that based on integrating of RT-Delphi, structural analysis, knowledge-based and explanation modeling capabilities. We applied...
Article
Full-text available
Decisions are made for the future, Futures Studies investigate possible fan of futures scenarios and its probabilities for easier decision making processes, taking into consideration unprecedented future events (wildcards) for clear vision of the future. Markov Chain method generally used as a mean of characterizing or summarizing data and of proje...
Conference Paper
Full-text available
In this paper we tackle the overbooking problem in hotel revenue management (RM). We propose a simulations­ based approach for the overbooking problem. It is based on accurately estimating all the hotel's processes, such as reservations arrivals, cancelations, length of stay, demand seasonality, etc. Subsequently, all these processes are simulated...
Conference Paper
Full-text available
This paper proposes a simulation framework that can enhance an organization performance via integrating Conjoint Analysis, System Dynamics and Stochastic Optimization. There are two main types of decisions controlled by the decision-maker; i.e. setting the price, and enhancing the quality of three main effective factors in the product or service st...
Conference Paper
Full-text available
Policy/decision makers in governments, corporations and institutions all need to anticipate the future, analysis its impacts and be confidence about the consensus results. Future studies methods are often made to utilize quantitative and qualitative approaches using various methods such as Trend Impact Analysis (TIA). This paper introduces advanced...
Article
Full-text available
In this article we propose a new dynamic pricing approach for the hotel revenue management problem. The proposed approach is based on having ‘price multipliers’ that vary around ‘1’ and provide a varying discount/premium over some seasonal reference price. The price multipliers are a function of certain influencing variables (for example, hotel occ...
Article
Full-text available
In this paper, a novel algorithm is proposed for sampling from discrete probability distributions using the probability proportional to size sampling method, which is a special case of Quota sampling method. The motivation for this study is to devise an efficient sampling algorithm that can be used in stochastic optimization problems --when there i...
Conference Paper
Full-text available
In this paper we propose a new unconstraining method for demand forecasting. Since true demand forecasting is a key aspect of hotel room revenue management systems, inaccurate forecasts will significantly impact the performance of these systems. We propose a method based on a Monte Carlo simulation forecasting model and an Expectation-Maximization...
Article
Full-text available
Interest in the topic of supply chain performance measurement has notably increased in the last two decades and considerable research has been conducted in this area. The objective of this paper is not just to review the advancements in theory on supply chain performance measurement per se, but rather to provide a taxonomy with which research in th...
Article
Full-text available
Improving supply chain performance has become a critical issue for gaining a competitive edge for companies. Many critical drawbacks prevent the existing performance measurement systems from making a significant contribution to the development and improvement of supply chain management and thus, several research is still needed in this area. In an...
Conference Paper
Full-text available
This work presents an Ant Colony Optimization-based approach to feature selection that works in tandem with an ACO classifier (Ant-Miner) in a wrapper approach to improve the classification accuracy of the Ant-Miner with a small and appropriate feature subset. The objective is to analyze the performance of five ACO algorithms on the feature selecti...
Article
Full-text available
This paper addresses the problem of room pricing in hotels. We propose a hotel revenue management model based on dynamic pricing to provide hotel managers with a flexible and efficient decision support tool for room revenue maximization. The two pillars of the proposed framework are a novel optimization model, and a multi-class scheme similar to th...
Article
Full-text available
Purpose – This paper aims to present an integrated framework for hotel revenue room maximization. The revenue management (RM) model presented in this work treats the shortcomings in existing systems. In particular, it extends existing optimization techniques for hotel revenue management to address group reservations and uses “forecasted demand” arr...