Mohamed A. Tawhid and Kevin B. Dsouza
In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed…
Abstract
In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed algorithm is called Hybrid Binary Bat Enhanced Particle Swarm Optimization Algorithm (HBBEPSO). In the proposed HBBEPSO algorithm, we combine the bat algorithm with its capacity for echolocation helping explore the feature space and enhanced version of the particle swarm optimization with its ability to converge to the best global solution in the search space. In order to investigate the general performance of the proposed HBBEPSO algorithm, the proposed algorithm is compared with the original optimizers and other optimizers that have been used for feature selection in the past. A set of assessment indicators are used to evaluate and compare the different optimizers over 20 standard data sets obtained from the UCI repository. Results prove the ability of the proposed HBBEPSO algorithm to search the feature space for optimal feature combinations.
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Xiao-jun Wang, Jian-yun Zhang, Shamsuddin Shahid, Lang Yu, Chen Xie, Bing-xuan Wang and Xu Zhang
The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological…
Abstract
Purpose
The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.
Design/methodology/approach
The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.
Findings
The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 108 to 62.20 × 108 m3 in year 2020 and between 73.32 × 108 and 89.27 × 108 m3 in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.
Originality/value
The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.
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Bo Yan, Xiao-hua Wu, Bing Ye and Yong-wang Zhang
The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper…
Abstract
Purpose
The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.
Design/methodology/approach
A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.
Findings
The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.
Practical implications
Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.
Originality/value
This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.
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Nianfei Gan, Miaomiao Zhang, Bing Zhou, Tian Chai, Xiaojian Wu and Yougang Bian
The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.
Abstract
Purpose
The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.
Design/methodology/approach
To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.
Findings
Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.
Originality/value
It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.
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Hui Guo, Jinzhou Jiang, Suoting Hu, Chun Yang, Qiqi Xiang, Kou Luo, Xinxin Zhao, Bing Li, Ziquan Yan, Liubin Niu and Jianye Zhao
The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap…
Abstract
Purpose
The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap between the main bridge and the approach bridge. For long-span railway bridges, it must also be coordinated with rail expansion joint (REJ), which is necessary to accommodate the expansion and contraction of, and reducing longitudinal stress in, the rails. The main aim of this study is to present analysis of recent developments in the research and application of BEJs in high-speed railway (HSR) long-span bridges in China, and to propose a performance-based integral design method for BEJs used with REJs, from both theoretical and engineering perspectives.
Design/methodology/approach
The study first presents a summary on the application and maintenance of BEJs in HSR long-span bridges in China representing an overview of their state of development. Results of a survey of typical BEJ faults were analyzed, and field testing was conducted on a railway cable-stayed bridge in order to obtain information on the major mechanical characteristics of its BEJ under train load. Based on the above, a performance-based integral design method for BEJs with maximum expansion range 1600 mm (±800 mm), was proposed, covering all stages from overall conceptual design to consideration of detailed structural design issues. The performance of the novel BEJ design thus derived was then verified via theoretical analysis under different scenarios, full-scale model testing, and field testing and commissioning.
Findings
Two major types of BEJs, deck-type and through-type, are used in HSR long-span bridges in China. Typical BEJ faults were found to mainly include skewness of steel sleepers at the bridge gap, abnormally large longitudinal frictional resistance, and flexural deformation of the scissor mechanisms. These faults influence BEJ functioning, and thus adversely affect track quality and train running performance at the beam end. Due to their simple and integral structure, deck-type BEJs with expansion range 1200 mm (± 600 mm) or less have been favored as a solution offering improved operational conditions, and have emerged as a standard design. However, when the expansion range exceeds the above-mentioned value, special design work becomes necessary. Therefore, based on engineering practice, a performance-based integral design method for BEJs used with REJs was proposed, taking into account four major categories of performance requirements, i.e., mechanical characteristics, train running quality, durability and insulation performance. Overall BEJ design must mainly consider component strength and the overall stiffness of BEJ; the latter factor in particular has a decisive influence on train running performance at the beam end. Detailed BEJ structural design must stress minimization of the frictional resistance of its sliding surface. The static and dynamic performance of the newly-designed BEJ with expansion range 1600 mm have been confirmed to be satisfactory, via numerical simulation, full-scale model testing, and field testing and commissioning.
Originality/value
This research provides a broad overview of the status of BEJs with large expansion range in HSR long-span bridges in China, along with novel insights into their design.
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Yuqin Wang, Bing Liang, Wen Ji, Shiwei Wang and Yiqiang Chen
In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors…
Abstract
Purpose
In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors, and learners all over the world can get access to these courses via the internet. However, faced with massive courses, learners often waste much time finding courses they like. This paper aims to explore the problem that how to make accurate personalized recommendations for MOOC users.
Design/methodology/approach
This paper proposes a multi-attribute weight algorithm based on collaborative filtering (CF) to select a recommendation set of courses for target MOOC users.
Findings
The recall of the proposed algorithm in this paper is higher than both the traditional CF and a CF-based algorithm – uncertain neighbors’ collaborative filtering recommendation algorithm. The higher the recall is, the more accurate the recommendation result is.
Originality/value
This paper reflects the target users’ preferences for the first time by calculating separately the weight of the attributes and the weight of attribute values of the courses.
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Jiansen Zhao, Xin Ma, Bing Yang, Yanjun Chen, Zhenzhen Zhou and Pangyi Xiao
Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles…
Abstract
Purpose
Since many global path planning algorithms cannot achieve the planned path with both safety and economy, this study aims to propose a path planning method for unmanned vehicles with a controllable distance from obstacles.
Design/methodology/approach
First, combining satellite image and the Voronoi field algorithm (VFA) generates rasterized environmental information and establishes navigation area boundary. Second, establishing a hazard function associated with navigation area boundary improves the evaluation function of the A* algorithm and uses the improved A* algorithm for global path planning. Finally, to reduce the number of redundant nodes in the planned path and smooth the path, node optimization and gradient descent method (GDM) are used. Then, a continuous smooth path that meets the actual navigation requirements of unmanned vehicle is obtained.
Findings
The simulation experiment proved that the proposed global path planning method can realize the control of the distance between the planned path and the obstacle by setting different navigation area boundaries. The node reduction rate is between 33.52% and 73.15%, and the smoothness meets the navigation requirements. This method is reasonable and effective in the global path planning process of unmanned vehicle and can provide reference to unmanned vehicles’ autonomous obstacle avoidance decision-making.
Originality/value
This study establishes navigation area boundary for the environment based on the VFA and uses the improved A* algorithm to generate a navigation path that takes into account both safety and economy. This study also proposes a method to solve the redundancy of grid environment path nodes and large-angle steering and to smooth the path to improve the applicability of the proposed global path planning method. The proposed global path planning method solves the requirements of path safety and smoothness.
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Muhammad Yazrin Yasin, Muhammad Azmi Bin Mohd Zain and Muhammad Haniff Bin Hassan
This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the…
Abstract
This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the factors that make it a competitive and fiscally sound entity. When considering urban development and redevelopment, we consider how proposed and ongoing projects, as well as plans, hierarchical links, and road networks, contributed to the increase. Because there is no urban growth boundary, land use change and rural encroachment, as well as environmental degradation and the impact of national economic projects on urban expansion, are both rapid and linear in the analysis. This paper also considers how to manage linear development that results in the creation of new suburbs. Finally, we propose strategies for achieving sustainable urban expansion and management by balancing the financial and governance capacities of Greater Kuala Lumpur local governments.
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The belt and road initiative (BRI) emanates from China and seeks to connect Europe, Asia and Africa through transport and telecommunications infrastructure. Despite the importance…
Abstract
Purpose
The belt and road initiative (BRI) emanates from China and seeks to connect Europe, Asia and Africa through transport and telecommunications infrastructure. Despite the importance of Africa in the BRI network, very little research has been done on the BRI in Africa, and even less of this emanates from Africa itself. In particular, considering that the BRI investments in Africa are largely transport related, there is almost no research covering the area of logistics, which should be greatly affected by the infrastructure investments. This paper sought to establish the current state of logistics research related to the BRI in Africa.
Design/methodology/approach
A bibliometric analysis was conducted on documents extracted from the SCOPUS database.
Findings
The findings indicate that there is a lack of research in critical areas such as environmental, social and economic impact of BRI transport investments, governance, logistics performance and international cooperation. In particular, there is a massive gap in local knowledge regarding the BRI.
Research limitations/implications
The study is limited to published research indexed in the SCOPUS database. Future research directions include empirical studies into BRI project initiation investigation, economic and environmental impacts, governance structures and policy intervention requirements and macro-level logistics impacts.
Practical implications
The study emphasises the importance publishing all the relevant information regarding BRI related projects in Africa to create transparency.
Originality/value
The study investigates the current research on the effect of China's BRI on transport and logistics in Africa through a bibliometric analysis. The investigation reveals that while there are huge investments in infrastructure, the actual effect on logistics of participating countries in Africa has not been interrogated.
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Ke Wang, Zheming Yang, Bing Liang and Wen Ji
The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in…
Abstract
Purpose
The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently.
Design/methodology/approach
In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices.
Findings
Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level.
Originality/value
This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.