Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications

Real world environments are characterized by high levels of linguistic and numerical uncertainties. A Fuzzy Logic System (FLS) is recognized as an adequate methodology to handle the uncertainties and imprecision available in real world environments and applications. Since the invention of fuzzy logic, it has been applied with great success to numerous real world applications such as washing machines, food processors, battery chargers, electrical vehicles, and several other domestic and industrial appliances. The first generation of FLSs were type-1 FLSs in which type-1 fuzzy sets were employed. Later, it was found that using type-2 FLSs can enable the handling of higher levels of uncertainties. Recent works have shown that interval type-2 FLSs can outperform type-1 FLSs in the applications which encompass high uncertainty levels. However, the majority of interval type-2 FLSs handle the linguistic and input numerical uncertainties using singleton interval type-2 FLSs that mix the numerical and linguistic uncertainties to be handled only by the linguistic labels type-2 fuzzy sets. This ignores the fact that if input numerical uncertainties were present, they should affect the incoming inputs to the FLS. Even in the papers that employed non-singleton type-2 FLSs, the input signals were assumed to have a predefined shape (mostly Gaussian or triangular) which might not reflect the real uncertainty distribution which can vary with the associated measurement. In this paper, we will present a new approach which is based on an adaptive non-singleton interval type-2 FLS where the numerical uncertainties will be modeled and handled by non-singleton type-2 fuzzy inputs and the linguistic uncertainties will be handled by interval type-2 fuzzy sets to represent the antecedents’ linguistic labels. The non-singleton type-2 fuzzy inputs are dynamic and they are automatically generated from data and they do not assume a specific shape about the distribution associated with the given sensor. We will present several real world experiments using a real world robot which will show how the proposed type-2 non-singleton type-2 FLS will produce a superior performance to its singleton type-1 and type-2 counterparts when encountering high levels of uncertainties.</jats:p

A Type-2 Fuzzy Logic Based System for Decision Support to Minimize Financial Default in the Sudanese Banking Sector

The recent global financial-economic crisis has led to the collapse of several companies from all over the world. This has created the need for powerful frameworks which can predict and reduce the potential risks in financial applications. Such frameworks help organizations to enhance their services quality and productivity as well as reducing the financial risk. The widely used techniques to build predictive models in the financial sector are based on statistical regression, which is deployed in many financial applications such as risk forecasting, customers’ loan default and fraud detection. However, in the last few years, the use of Artificial Intelligence (AI) techniques has increased in many financial institutions because they can provide powerful predictive models. However, the vast majority of the existing AI techniques employ black box models like Support Vector Machine (SVMs) and Neural Network (NNs) which are not able to give clear and transparent reasoning to explain the extracted decision. However, nowadays transparent reasoning models are highly needed for financial applications. This paper presents a type-2 fuzzy logic system for predicting default in financial systems. the researchers used a real dataset collected from the banking sector in Sudan. The proposed system resulted in transparent outputs which could be easily understood, analyzed and augmented by the human stakeholders. Besides, the proposed system resulted in an average recall of 83.5%, which outperformed its type-1 counterpart by 20.66%

A Type-2 Fuzzy Logic Based System for Malaria Epidemic Prediction in Ethiopia

Malaria is the most prevalent mosquito-borne disease throughout tropical and subtropical regions of the world with severe medical, economic, and social impact. Malaria is a serious public health problem in Ethiopia since 1959, even if, its morbidity and mortality have been reduced starting from 2001. Various studies were conducted to predict the malaria epidemic using mathematical and statistical approaches, nevertheless, they had no learning capabilities. In this paper, we present a Type-2 Fuzzy Logic Based System for Malaria epidemic prediction in Ethiopia which was trained using real data collected throughout Ethiopia from 2013 to 2017. Fuzzy Logic Based Systems provide a transparent model which employs IF-Then rules for the prediction that could be easily analyzed and interpreted by decision-makers. This is quite important to fight the sources of Malaria and take the needed preventive measures where the generated rules from our system were able to explain the situations and intensity of input factors which contributed to Malaria epidemic incidence up to three months ahead. The presented Type-2 Fuzzy Logic System (T2FLS) learns its rules and fuzzy set parameters from data and was able to outperform its counterparts T1FLS in 2% and ANFIS in 0.33% in the accuracy of prediction of Malaria epidemic in Ethiopia. In addition, the proposed system did shed light on the main causes behind such outbreaks in Ethiopia because of its high level of interpretabilit

Intelligent Association Exploration and Exploitation of Fuzzy Agents in Ambient Intelligent Environments

This paper presents a novel fuzzy-based intelligent architecture that aims to find relevant and important associations between embedded-agent based services that form Ambient Intelligent Environments (AIEs). The embedded agents are used in two ways; first they monitor the inhabitants of the AIE, learning their behaviours in an online, non-intrusive and life-long fashion with the aim of pre-emptively setting the environment to the users preferred state. Secondly, they evaluate the relevance and significance of the associations to various services with the aim of eliminating redundant associations in order to minimize the agent computational latency within the AIE. The embedded agents employ fuzzy-logic due to its robustness to the uncertainties, noise and imprecision encountered in AIEs. We describe unique real world experiments that were conducted in the Essex intelligent Dormitory (iDorm) to evaluate and validate the significance of the proposed architecture and methods

STUDY AND PUBLICATION OF A COLLECTION OF CHINESE METAL ARTIFACTS WITH ISLAMIC SCRIPTS PRESERVED IN THE BEIJING NIUJIE MOSQUE

دراسة ونشر مجموعة من التحف المعدنية الصينية ذات الكتابات الإسلامية محفوظة في مسجد نيوجيه ببكين [Ar] تهدف هذه الدراسة إلى نشر وفحص ودراسة مجموعة لم تنشر من قبل لأربعة من التحف المعدنية الصينية ذات الكتابات الإسلامية والمحفوظة في مسجد نيوجيه، أقدم مسجد في بكين. تعود هذه الأواني إلى عصر أسرتي مينغ (1368-1644م) وتشينغ (1644-1912م) الحاكمة للصين، مؤرخة بخراطيش كتابية تحمل أسماء كل من الإمبراطور شواندا (1425-1435م) والامبراطور جياتشينغ (1796-1820 م) والامبراطور كانغشي (1661-1722) والامبراطور تشيان لونغ (1735-1796). تحاول هذه الدراسة شرح الأساليب الفنية والمواد الخام الخاصة بالمجموعة، وكذلك الزخارف التي اتسمت بالثراء والتنوع، كما تسعى الدراسة إلى استكشاف تاريخ المسلين الصينيين عبر فحص تلك المجموعة؛ إذ حوت إحدى القطع على نص صيني يشير إلى علاقة البلاط الصيني بالمجتمع المسلم المحلي في مدينة بكين؛ لذا فهذه القطع تعد وثائق مهمة تسجل مرحلة مهمة في تاريخ الإسلام في الصين خلال عصر أسرتي مينغ تشينغ. تسبب كلا من الطلب الخارجي والداخلي على هذا النوع من الفن الذي يحمل الكتابات العربية والصينية في انتشاره في الصين، وهو دليل لا يرقى إليه الشك على عظم التأثيرات الفنية المتبادلة بين الفنين الصيني الإسلامي، وإشارة تؤكد على أن الفن الإسلامي تجاوز الحدود حتى وصل إلى أقصى شرق آسيا..[En] This study aims to publish, examine and study a group of four Chinese Islamic metal artifacts preserved in Niujie Mosque, the oldest mosque in Beijing. These artifacts date back to the Ming (1368-1644 AD) and Qing (1644-1912 AD) dynasties. They are dated by cartouches bearing the names of Emperors Xuanda (1425-1435 AD), Jiaqing (1796-1820 AD), Kangxi (1661-1722 AD), and Qianlong (1735-1796 AD). This study attempts to explain the artistic methods and raw materials of the collection, as well as the decorations that were characterized by richness and diversity. The study also seeks to explore the history of Chinese worshipers through examining that group. One of the objects contained a Chinese text referring to the Chinese court’s relationship with the local Muslim community in the city of Beijing. Therefore, it is an important document that records an important stage in the history of Islam in China during the Ming and Qing dynasties. Both external and internal demand for this type of art that carries Arabic and Chinese writings caused its spread in China, which is indubitable evidence of the great mutual artistic influences between the Chinese and Islamic arts, and an indication that confirms that Islamic art crossed borders until it reached Far East Asia

Toward Human-Understandable, Explainable AI

Recent increases in computing power, coupled with rapid growth in the availability and quantity of data have rekindled our interest in the theory and applications of artificial intelligence (AI). However, for AI to be confidently rolled out by industries and governments, users want greater transparency through explainable AI (XAI) systems. The author introduces XAI concepts, and gives an overview of areas in need of further exploration-such as type-2 fuzzy logic systems-to ensure such systems can be fully understood and analyzed by the lay user

A multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization

In industries which employ large numbers of mobile field engineers (resources), there is a need to optimize the task allocation process. This particularly applies to utility companies such as electricity, gas and water suppliers as well as telecommunications. The process of allocating tasks to engineers involves finding the optimum area for each engineer to operate within where the locations available to the engineers depends on the work area she/he is assigned to. This particular process is termed as work area optimization and it is a sub-domain of workforce optimization. The optimization of resource scheduling, specifically the work area in this instance, in large businesses can have a noticeable impact on business costs, revenues and customer satisfaction. In previous attempts to tackle workforce optimization in real world scenarios, single objective optimization algorithms employing crisp logic were employed. The problem is that there are usually many objectives that need to be satisfied and hence multi-objective based optimization methods will be more suitable. Type-2 fuzzy logic systems could also be employed as they are able to handle the high level of uncertainties associated with the dynamic and changing real world workforce optimization and scheduling problems. This paper presents a novel multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization, which was employed in real world scheduling problems. This system had to overcome challenges, like how working areas were constructed, how teams were generated for each new area and how to realistically evaluate the newly suggested working areas. These problems were overcome by a novel neighborhood based clustering algorithm, sorting team members by skill, location and effect, and by creating an evaluation simulation that could accurately assess working areas by simulating one day's worth of work, for each engineer in the working area, while taking into account uncertainties. The results show strong improvements when the proposed system was applied to the work area optimization problem, compared to the heuristic or type-1 single objective optimization of the work area. Such optimization improvements of the working areas will result in better utilization of the mobile field workforce in utilities and telecommunications companies

An Ancient Mosque in Ningbo, China “Historical and Architectural Study”

With the rise of Tang dynasty (618–907), Ningbo was an important commercial city on the Chinese eastern coast. Arab merchants had an important role in trade relations between China and the West. Ningbo mosque was initially built in 1003 during Northern Song period by Muslims traders who had migrated from Arab lands to settle in China. Through ongoing research of representative Muslim architecture, such as Chinese Mosques, this paper seeks to shed light on the artistic features of this mosque. Many of the key characteristics of this distinctive ethnic heritage are based on commonly held religious beliefs and on the relationship between culture and religion. This paper aims to study the characteristics of Chinese mosques architecture, through studying one of the most important planning patterns of the traditional courtyards plan Known as Siheyuan, and it will also make a practical study on Ningbo Yuehu Mosque. The result of this study shows that the Ningbo Yuehu mosque is like Chinese mosques which follows essentially the norms of Chinese planning, layout design, and wooden structures

Employing zSlices based general type-2 fuzzy sets to model multi level agreement

In this paper, we introduce the concept of Multi Level Agreement (MLA) based on (zSlices based) general type-2 fuzzy sets. We define the notion of MLA and describe how it can be computed based on a series of interval type-2 fuzzy sets. We provide examples, visualizing the nature of MLA sets and discuss their properties and interpretation. Moreover, we specifically address the reason for introducing MLA in order to allow the modeling of agreement in real world applications using fuzzy sets while still maintaining an uncertainty model and show that the use of general type-2 fuzzy sets is essential for MLA as classical sets, type-1 and interval type-2 fuzzy sets do not provide a degree of freedom which could be employed to model agreement. © 2011 IEEE

Static vs. Dynamic List-Scheduling Performance Comparison

The problem of efficient task scheduling is one of the most important and most difficult issues in homogeneous computing environments. Finding an optimal solution for a scheduling problem is NP-complete. Therefore, it is necessary to have heuristics to find a reasonably good schedule rather than evaluate all possible schedules. List-scheduling is generally accepted as an attractive approach, since it pairs low complexity with good results. List-scheduling algorithms schedule tasks in order of priority. This priority can be computed either statically (before scheduling) or dynamically (during scheduling). This paper presents the characteristics of the two main static and the two main dynamic list-scheduling algorithms. It also compares their performance in dealing with random generated graphs with various characteristics