The surveillance and reports on accidents for the current traffic management are carried out by viewing and inspecting CCTV footage. This method is slow to detect incidents and requires a lot of manpower. Since nowadays communication technology and social media play a role in reporting such incidents this research has been conducted to investigate accidents of interest from text messages reported on social media in Thai. There is currently no research or platform that supports this type of work clearly. This research presented the development of a neuron network memory-learning model to solve the problem of incidence pattern classification and incidence severity identification from social media messages in Thai. Using deep learning models such as MLP CNN Bi-LSTM and LSTM+CNN the study was designed and divided into three experimental patterns. This included examining patterns to identify traffic incidents that may be reported as general news or traffic reporting; examining patterns to indicate the type of incidents such as traffic accidents disasters damaged roads or others other than those mentioned; and examining patterns to specify the severity levels of the incidents such as normal intermediate traffic lane blocking or immovable. The experiments demonstrated the capability of CNN+LSTM learning models with the best incidence detection result at 93.44 %. The CNN model gave the best result in identifying a pattern of incidence at 85.29 % and the LSTM model was best able to determine the severity levels of the incidence at 88.53 %.

This study Motorcycle Tourism Potential of Kanchanaburi Province aims to study the motorbike tourism potential of Kanchanaburi. And suggestions for motorbike tourism development in Kanchanaburi Province. The research employed a quantitative research. The research sample was 400 tourists who travel by motorbike in Kanchanaburi tourist attractions. The research tools was a questionnaire with open-ended questions. The data is described by frequency percentage and standard deviation. Most participants were male 30-39 years old had obtained a bachelor degree managed private businesses and earned income of naked motorcycle. The results of the research indicate that opinions about motorcycle tourism potential in Kanchanaburi Province ranked from the highest to the lowest potential is travel cost Presentation and information view and the biker challenge of the route Security facilities of motorcycle tourism policy tourist attractions people motorcycle group and motorcycle club and marketing. Suggestions on motorcycle Tourism development in Kanchanaburi. There are 8 points: price control public relations adding motorcycle rest area ensure safe travels adding motorcycle tourism services establish regulations related to Motorcycle tourism conservation of tourist attractions and Promote activities in Motorcycle group.

The urban and economic areas in Bangkok at present are grown rapidly. The travelling and road usage are increased which make the traffic jam problem happened and result the economics and social loss. Accordingly it is necessary to study the state of traffic and transportation to make the planning and define the ways to solve the problem via physical conditions or light signals. Not only the current problem s but also suggest the way to solve the problem which may happen in the future. This research studied about traffic volumes and physical conditions at Khae Rai Intersection. The real traffic is simulated by NETSIM program from the traffic volumes and physical conditions data which are collected to examine and analyze the effects from the traffic and suggest the ways to solve the problems. The results showed that NETSIM program can be used for simulating before and after traffic condition at Khae Rai Intersection. The conclusion showd the better traffic condition after it was solved by light signals and physical conditions

ไม่ปรากฏบทคัดย่อ