Implementation Of Intelligent Algorithm Research Articles

Enhancing operational performance: The impact of smart algorithms in Saudi Arabian sports facilities

The objective of this study was to examine the impact of utilizing smart algorithms on enhancing the operational performance of sports facilities in the Kingdom of Saudi Arabia. These algorithms, based on principles and concepts of artificial intelligence, aim to achieve functions such as learning, decision-making, data analysis, pattern recognition, planning, and problem-solving. The study aimed to identify the extent to which smart algorithms are utilized in sports facilities, assess the level of operational performance, explore the correlation between the use of smart algorithms and operational performance, and predict the level of operational performance based on the use of smart algorithms. The study employed a descriptive approach, specifically utilizing a survey study method. Participants included chairmen and members of boards of directors, executive directors, sports directors, administrators, specialists, and members of various committees. The study sample was intentionally selected from different categories within the study population. Two questionnaires were used to collect data from 325 participants. The findings revealed a lack of utilization of smart algorithms in sports facilities in the Kingdom of Saudi Arabia, indicating a low level of operational performance. Additionally, a correlation was observed between the use of smart algorithms and operational performance, suggesting that the level of operational performance can be predicted based on the utilization of smart algorithms. The study concludes that the implementation of intelligent algorithms can enhance the operational performance of sports facilities in the Kingdom of Saudi Arabia. It provides valuable insights into the effects of utilizing smart algorithms on improving operational performance.

Intelligent algorithms and methodologies for low‐carbon smart manufacturing: Review on past research, recent developments and future research directions

AbstractSignificant attention has been given to low‐carbon smart manufacturing (SM) as a strategy for promoting sustainability and carbon‐free emissions in the manufacturing industry. The implementation of intelligent algorithms and procedures enables the attainment and enhancement of low‐carbon clever manufacturing processes. These algorithms facilitate real‐time monitoring and predictive maintenance, ensuring efficient and sustainable operations and data‐driven decision‐making, increasing resource utilisation, waste reduction, and energy efficiency. The research examines the utilisation of algorithms in the context of low‐carbon smart manufacturing, encompassing machine learning, optimisation algorithms, and predictive analytics. A comprehensive literature evaluation spanning from 2011 to 2023 is conducted to assess the significance of low‐carbon approaches in the context of smart manufacturing. An integrated approach is used using content analysis, network data analysis, bibliometric analysis, and cluster analysis. Based on the published literature the leading contributors to low‐carbon manufacturing research are India, China, United States, United Kingdom, Singapore, and Italy. The results have shown five main themes—Low‐carbon smart manufacturing and applications of Algorithms; Industry 4.0 technologies for low‐carbon manufacturing; low carbon and green manufacturing; Low‐carbon Manufacturing, and Product design and control; Lean Systems and Smart Manufacturing. The purpose of this study is to provide policymakers and researchers with a guide for the academic development of low‐carbon manufacturing by evaluating research efforts in light of identified research deficits.

A Method for the Design of Bicomplex Orthogonal DSP Algorithms for Applications in Intelligent Radio Access Networks

In this paper, a new method for designing orthogonal bicomplex digital signal processing (DSP) algorithms is developed. In contrast to those previously reported on, the method proposed is universal, since it is not affected by the order or the type of the real digital processing algorithm employed as a prototype. The method is based on a transformation starting with either real or complex orthogonal DSP algorithms represented in the z-domain, and transforming them into orthogonal bicomplex algorithms. The proposed new method is applied in the design of bilinear orthogonal bicomplex DSP systems with a canonical number of elements, the main advantage of which is that the order of the digital system is reduced by a factor of four. As well as being canonical, the orthogonal bicomplex digital systems are also symmetrical structures, as a result of which they offer parallelism and subsequent unification. It is experimentally shown that bicomplex orthogonal DSP algorithms acquire the properties of the initial algorithm prototype, irrespective of whether it is real or complex. Since the new design method is universally applicable, it can be used to develop bicomplex orthogonal digital algorithms of any order and type. Being simple, canonical, and symmetrical—and, thus, leading to lower equipment cost, reduced complexity, and higher energy efficiency—these structures may well be appropriate for the enhancement of the implementation of intelligent algorithms in next-generation radio access networks.