scholarly journals Carbon Footprint and Total Fuel Consumption Benefit Evaluation of a Proposed Decision Support System Algorithm for Istanbul Ataturk Airport Surface Movement Area

2020 ◽  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Fuel Consumption ◽  
Carbon Footprint ◽  
Support System ◽  
Surface Movement ◽  
Benefit Evaluation ◽  
Fuel Consumption Benefit ◽  
Consumption Benefit ◽  
Total Fuel Consumption

An Automated Energy Conservation Decision Support System for Navy Gas Turbines

2010 ◽  
Author(s):  
Michael J. Roemer ◽  
Carl A. Palmer ◽  
Sudarshan P. Bharadwaj ◽  
Chris Savage
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Energy Conservation ◽  
Real Time ◽  
Fuel Consumption ◽  
Support System ◽  
Gas Turbines ◽  
Fuel Management ◽  
Real Time Information ◽  
Time Information

Energy conservation measures currently employed by U.S. Navy surface combatants require labor-intensive, time-consuming data entry from which fuel curves are generated to drive each ship’s propulsion plant machinery alignment. From these rudimentary curves optimal transit speeds, configurations, and refueling requirements are determined for specific operational demands and mission profiles. This paper describes an automated process for optimizing shipboard fuel consumption rates by integrating advanced diagnostic and maintenance optimization techniques with the onboard data information system. The automated energy conservation decision support system described herein addresses fossil fuel propulsion (gas turbines, steam turbines, and diesel engines), power generation and auxiliary systems. The software tool consists of diagnostic, fuel management, and maintenance modules. The diagnostic module tracks and trends the health state of components that use fuel (and their supporting systems) to provide real-time information on the impact of their current condition on fuel consumption. The fuel management module automates data collection and the generation of fuel curves through open-systems architecture communication with ICAS. It also enables planning by recommending an optimal machinery configuration to minimize fuel consumption based on either speed or time to destination constraints. Additionally, a fuel management module provides real-time information on fuel consumption and optimizes the load of each component based on its health condition, operating requirements and the number and condition of similar components. Finally, overall decision support comes from the maintenance management module that tracks the maintenance actions being performed on fuel consuming systems and recommends future maintenance to be performed (from a fuel conservation standpoint) based on current health information.

scholarly journals IMPLEMENTASI METODE ANALYTICAL HIERARCHY PROCESS (AHP) PADA SISTEM PENDUKUNG KEPUTUSAN PEMBELIAN MOBIL DI BANDAR LAMPUNG

2020 ◽  
Vol 7 (3) ◽  
pp. 219
Author(s):  
Admi Syarif ◽  
Ari Ardianto ◽  
Bambang Hermanto ◽  
Machudor Yusman
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Fuel Consumption ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
Daily Life ◽  
Web Based ◽  
Hierarchy Process ◽  
The Web

<p><em>Car is an important transportation to support many activities in our daily life. There have been many variations of car based on models, price, specifications and so on. This study aims to implement the web-based Analytical Hierarchy Process (AHP) to recommend a car based on some criteria. The decision is done based on the following criteria as price, brand, cylinder capacity, fuel consumption, and passenger capacity. We used the data of 254 model variants car from six famous brands (Toyota, Daihatsu, Mitsubishi, Honda, Suzuki, and Nissan). The experiments have been to see the effectivity of the proposed method by giving different weight priority value . The results show that the method work well to give recommendation that suits consumers' desires.</em></p><p><em><strong>Keywords</strong></em><em>: Analytical Hierarchy Process, Car, Decision Support System,</em><em> MCDM.</em></p><p><em>Mobil merupakan alat transportasi yang penting saat ini guna menunjang aktivitas maupun untuk memenuhi gaya hidup seseorang. </em><em>Ada beragam jenis  mobil dengan </em><em>model</em><em>, merk</em><em> dan spesifikasi</em><em> tehnis lainnya. </em><em>Penelitian ini bertujuan mengimplementasikan metode AHP</em><em> berbasis web</em><em>  untuk membantu merekomendasikan mobil yang sesuai dengan keinginan konsumen. </em><em>R</em><em>ekomendasi keputusan </em><em>berbasisi 6 (enam) </em><em>kriteria diantaranya harga, merk, kapasitas silinder, konsumsi BBM, dan kapasitas penumpang. </em><em>Eksperimen  dilakukan dengan menggunakan d</em><em>ata 254 varian model mobil dengan enam merk</em><em> terkenal </em><em> </em><em>Toyota, Daihatsu, Mitsubishi, Honda, Suzuki, dan Nissan).</em><em> Hasil pengujian </em><em>sistem telah bekerja dengan sangat baik. P</em><em>embobotan kriteria dan pemilihan alternatif sangat berpengaruh terhadap rekomendasi keputusan.</em><em></em></p><p><em><strong>Kata kunci</strong></em><em>: </em><em>Analytical Hierarchy Process</em>, <em>Mobil, Sistem Pendukung Keputusan</em><em>, MCDM</em><em>.</em></p>

scholarly journals Applying artificial neural networks for modelling ship speed and fuel consumption

2020 ◽  
Vol 32 (23) ◽  
pp. 17379-17395 ◽  
Author(s):  
Wieslaw Tarelko ◽  
Krzysztof Rudzki
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Fuel Consumption ◽  
Support System ◽  
Ann Model ◽  
Data Set ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Ship Speed

AbstractThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making decisions regarding setting the proper commanded outputs to is extraordinarily difficult. To support such decisions, we have developed a decision support system. Its main elements are the ANN models enabling ship fuel consumption and speed prediction. To collect data needed for building ANN models, sea trials were conducted. In this paper, the decision support system concept, input and variables of the ship driveline system models, and data acquisition methods are presented. Based on them, we developed appropriate ANN models. Subsequently, we performed a quality assessment of the collected data set, data normalization and division of the data set, selection of an ANN model architecture and assessment of their quality.

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

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