This research aimed to use the extended theory of planned behaviour (TPB) to determine whether it can explain users' intention to use the bus-based park-and-ride (P&R) facilities in Putrajaya, Malaysia. This research introduced a new predictor related to the use of P&R facilities, namely trust. The survey involved 437 respondents. A structural equation model is used to show that trust positively influence the attitude and perceived behavioural control (PBC) towards the use of P&R facilities. However, the intention to use P&R facilities is not profoundly influenced by trust and subjective norm. Results also revealed that attitude, subjective norm, and PBC have a strong positive influence on the intention to use P&R facilities. In addition, several policy recommendations are discussed in this study. All things considered, the theory of planned behaviour was able to predict users' intention to use P&R facilities in Malaysia. It is hoped that this research would increase researchers' interest in conducting further investigation in this field and that the model is beneficial to service providers in helping them identify the factors that increase the number of P&R users.
Pembelajaran sistem pangkalan peraturan kabur menggunakan algoritma genetik mempunyai masa depan yang cerah bagi menyelesaikan beberapa masalah. Lojik kabur menawarkan cara sederhana bagi menyimpulkan maklumat input yang kasar, kabur, cacat atau tidak jelas. Model lojik kabur adalah berasaskan kaedah–kaedah empirik bergantung kepada pengalaman operator berbanding dengan pengetahuan teknikal daripada sistem. Dalam metod lojik kabur, sebarang input yang munasabah dapat diproses dan sebilangan output dapat dijana meskipun penakrifan pangkalan peraturan secara cepat dapat menjadi rumit sekiranya terlalu banyak input dan output yang dipilih untuk sebuah penggunaan. Bergantung kepada sistem, semakin rumit input dan output yang ingin diselesaikan oleh sistem, maka akan semakin banyak jumlah bilangan peraturan dan kerumitan tetapi juga akan menambah mutu kawalan dari sistem. Banyak kaedah telah dicadangkan bagi menjana peraturan kabur. Idea asas daripada penyelidikan ini adalah untuk mempelajari serta menjana peraturan paling optimum yang diperlukan bagi mengawal input tanpa mengurangi mutu kawalan. Kertas kerja ini yang mencadangkan penjanaan peraturan kabur menggunakan penggugusan subtraktif pada lojik kabur Takasi–Sugeno–Kang (TSK) bagi kegunaan kawalan lampu isyarat lalu lintas. Kata kunci: Lojik kabur TSK, sistem pangkalan peraturan kabur, teknik penggugusan subtraktif Learning fuzzy rule–based systems with genetic algorithms can lead to very useful descriptions of several problems. Fuzzy logic (FL) provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy or missing input information. The FL model is empirically based, relying on an operator’s experience rather than their technical understanding of the system. In the FL method, any reasonable number of inputs can be processed and numerous outputs will be generated, although defining the rule–base quickly becomes complex if too many inputs and outputs are chosen for a single implementation since rules defining their interrelations must also be defined. This will increase the number of fuzzy rules and complexity but may also increase the quality of the control. Many methods were proposed to generate fuzzy rules–base. The basic idea is to study and generate the optimum rules needed to control the input without compromising the quality of control. The paper proposed the generation of fuzzy rule base by subtractive clustering technique in Takagi–Sugeno–Kang (TSK) fuzzy method for traffic signal control system. Key words: TSK fuzzy logic, fuzzy rule base system, subtractive clustering technique
Abstract:In Malaysia, the rapid increase in the use of own transport prompted by inadequate public transport has resulted in increased traffic congestion, accidents, inadequate parking space and air pollution among other evils. This study sought to identify the factors preventing own transport users from shifting to public transport and to develop model shift from car to public transport in order to formulate the policies to achieve this. A survey was carried out on users of private and public (both bus and urban train transport) (n = 1350). Multinomial legit models were developed for the three alternative modes, Car, Bus and Train. This study found that the most important variables found likely to encourage the use of public transport were reduced travel time and subsidized fares. As expected, for the commuter to switch to public transport he would have to be incentivated to do so.
In order to understand travellers’ willingness to use the train in Petaling Jaya, this study adds four predictors - situational factors, trust, novelty seeking and external influence - to the existing model of theory of planned behaviour (TPB). The study collected research data from employees in Petaling Jaya, Malaysia, resulting in valuable data of 400 participants. Results indicate that attitude, perceived behavioural control, and subjective norm are found to have positive effects on the behavioural intention of taking the train. Furthermore, novelty seeking and external influence also have positive influences on attitude. While the three antecedents of trust were found to have an indirect positive effect on commuters’ intention to take the train via attitude, subjective norm and PBC. Situational factors were found to have an indirect negative significant influence on people’s intention to take the train through perceived behavioural control.
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